diff --git a/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_en.json b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_en.json new file mode 100644 index 00000000..aed6f1de --- /dev/null +++ b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_en.json @@ -0,0 +1,52 @@ +{ + "0_TextBox_0": "Slicer Welcome", + "1_TextBox_0": "Slicer Welcome", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "1_TextBox_1": "Sonia Pujol, Ph.D.", + "2_Goal_title": "Goal", + "6_WelcometoSlicer_title": "Welcome to Slicer", + "7_SlicerUserInterface_title": "Slicer User Interface", + "7_ArrowText_0": "Toolbar", + "7_TextBox_1": "3D viewer", + "7_ArrowText_6": "2D anatomical viewers", + "7_TextBox_5": "Data probe", + "0_TextBox_3": "Assistant Professor of Radiology\nBrigham and Women’s Hospital\nHarvard Medical School\n", + "1_TextBox_3": "Assistant Professor of Radiology\n\nBrigham and Women’s Hospital\n\nHarvard Medical School\n", + "2_Goal_body": "This tutorial is a short introduction to the Welcome module of the Slicer open-source software.", + "3_TextBox_0": "Slicer5 Basics", + "4_TextBox_0": "Slicer5 Basics", + "3_TextBox_1": "*Slicer is an open-source software for segmentation, registration and visualization of medical imaging data.\n*The platform is developed through a multi-institution effort of several NIH funded large-scale consortia.\n*Slicer is for medical research only, and is not FDA approved. ", + "4_TextBox_1": "3D Slicer 5 version 5.10.0 includes over 100 modules and more than 190 extensions for image segmentation, registration and 3D visualization of medical imaging data.", + "5_TextBox_0": "Supported Platforms", + "5_TextBox_1": "*Slicer is a multi-platform software developed and maintained on Mac OSX, Linux and Windows.\n\n*Slicer requires a minimum of 2 GB of RAM and a dedicated graphic accelerator with 64 MB of on-board graphic memory. ", + "6_TextBox_1": "Each module of Slicer includes a series of tabs, which give access to different functionalities.\n\nClick on the arrow symbol to display the content of each tab. ", + "7_TextBox_3": "User Interface (UI) panel of the Slicer Welcome Module", + "8_WelcomeModule_title": "Welcome Module", + "9_WelcomeModule_title": "Welcome Module", + "13_WelcomeModule_title": "Welcome Module", + "8_TextBox_1": "The Documentation & Tutorials tab contains links to the training compendium and documentation pages of 3D Slicer.", + "9_TextBox_0": "The Welcome module panel contains shortcuts for loading different types of data. A series of sample data are also available.\n\nClick on Download Sample Data to access the Sample Data Module", + "10_SampleData_title": "Sample Data", + "11_SampleData_title": "Sample Data", + "12_SampleData_title": "Sample Data", + "10_TextBox_1": "The Sample Data module contains links to different sample datasets that can be downloaded into Slicer.", + "11_TextBox_0": "Brain MR", + "11_TextBox_1": "Chest CT", + "11_TextBox_2": "Cardiac CT", + "11_TextBox_3": "Diffusion Tensor Imaging (DTI) Dataset", + "11_TextBox_4": "Brain MRI (tumor patient)", + "12_ArrowText_0": "Click on MRHead to download the\ndataset in Slicer.", + "13_TextBox_0": "The MR scan of the brain appears\nin the 2D viewers.", + "14_TextBox_0": "Position the mouse on the little pin icon in the top left corner of the red viewer to display the viewer menu", + "15_TextBox_1": "Click on the link icon to link all three 2D viewers, and on the eye icon next to it\nto display the slices in the 3D viewer", + "16_TextBox_0": "The axial, coronal and sagittal slices appear in the 3D viewer.\nGo back to the Welcome module using the green arrow in the toolbar", + "17_GoingFurther_title": "Going Further", + "18_TextBox_0": "Going Further", + "17_TextBox_0": "To learn more about Slicer and its different functionalities, visit the Slicer Compendium", + "18_TextBox_1": "https://training.slicer.org/", + "19_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n\nChan Zuckerberg Initiative (CZI)", + "14_MRBrainSampleDataset_title": "MR Brain Sample Dataset", + "15_MRBrainSampleDataset_title": "MR Brain Sample Dataset", + "16_MRBrainSampleDataset_title": "MR Brain Sample Dataset", + "19_TextBox_0": "Acknowledgements" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_es.json b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_es.json new file mode 100644 index 00000000..e98f1583 --- /dev/null +++ b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_es.json @@ -0,0 +1,65 @@ +{ + "0_TextBox_0": "Bienvenido a Slicer", + "1_TextBox_0": "Bienvenido a Slicer", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "1_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_2": "28/08/2024", + "0_TextBox_3": "Assistant Professor of Radiology\nBrigham and Women’s Hospital\nHarvard Medical School\n", + "2_Goal_title": "Meta", + "1_Goal_body": "Este tutorial es una breve introducción al módulo de bienvenida del software de código abierto Slicer. ", + "2_3DSlicerversion48_title": "3D Slicer versión 4.8", + "6_WelcometoSlicer_title": "Bienvenido a Slicer", + "3_TextBox_0": "Slicer5 Basics", + "7_SlicerUserInterface_title": "Interfaz de Usuario Slicer", + "4_TextBox_1": "3D Slicer 5 version 5.10.0 includes over 100 modules and more than 190 extensions for image segmentation, registration and 3D visualization of medical imaging data.", + "7_ArrowText_0": "B. Herramientas", + "7_TextBox_1": "Visor 3D", + "7_ArrowText_6": "Visores 2D anatómicos", + "7_TextBox_5": "Prueba de datos", + "1_TextBox_3": "Assistant Professor of Radiology\n\nBrigham and Women’s Hospital\n\nHarvard Medical School\n", + "2_Goal_body": "This tutorial is a short introduction to the Welcome module of the Slicer open-source software.", + "4_TextBox_0": "Slicer5 Basics", + "3_TextBox_1": "*Slicer is an open-source software for segmentation, registration and visualization of medical imaging data.\n*The platform is developed through a multi-institution effort of several NIH funded large-scale consortia.\n*Slicer is for medical research only, and is not FDA approved. ", + "5_TextBox_0": "La\tDocumentación y\tTutoriales\t\nlengüeta\tcontiene\tenlaces\tpara\tel\tentrenamiento\t\ncompendio\ty\tdocumentación páginas\tde\t3D\tSlicer\tversión\t4.8.\t", + "5_TextBox_1": "*Slicer is a multi-platform software developed and maintained on Mac OSX, Linux and Windows.\n\n*Slicer requires a minimum of 2 GB of RAM and a dedicated graphic accelerator with 64 MB of on-board graphic memory. ", + "6_TextBox_1": "Each module of Slicer includes a series of tabs, which give access to different functionalities.\n\nClick on the arrow symbol to display the content of each tab. ", + "7_TextBox_3": "User Interface (UI) panel of the Slicer Welcome Module", + "8_WelcomeModule_title": "Módulo Bienvenido", + "9_WelcomeModule_title": "Módulo Bienvenido", + "13_WelcomeModule_title": "Módulo Bienvenido", + "8_TextBox_1": "The Documentation & Tutorials tab contains links to the training compendium and documentation pages of 3D Slicer.", + "9_TextBox_0": "La resonancia magnética del cerebro aparece\nen los visores 2D.", + "10_SampleData_title": "Sample Data", + "11_SampleData_title": "Sample Data", + "12_SampleData_title": "Sample Data", + "10_TextBox_1": "The Sample Data module contains links to different sample datasets that can be downloaded into Slicer.", + "11_TextBox_0": "Pulse en el icono de enlace para vincular los tres\nvisores 2D y en el icono del ojo que se encuentra\njunto a él para mostrar los cortes en el visor 3D. );", + "11_TextBox_1": "Chest CT", + "11_TextBox_2": "Cardiac CT", + "11_TextBox_3": "Diffusion Tensor Imaging (DTI) Dataset", + "11_TextBox_4": "Brain MRI (tumor patient)", + "12_ArrowText_0": "Click on MRHead to download the\ndataset in Slicer.", + "13_TextBox_0": "Para obtener más información sobre Slicer y\nsus diferentes funcionalidades, visite el compendio de Slicer4.8", + "14_TextBox_0": "Position the mouse on the little pin icon in the top left corner of the red viewer to display the viewer menu", + "15_TextBox_1": "Click on the link icon to link all three 2D viewers, and on the eye icon next to it\nto display the slices in the 3D viewer", + "16_TextBox_0": "The axial, coronal and sagittal slices appear in the 3D viewer.\nGo back to the Welcome module using the green arrow in the toolbar", + "17_GoingFurther_title": "Going Further", + "18_TextBox_0": "Going Further", + "17_TextBox_0": "To learn more about Slicer and its different functionalities, visit the Slicer Compendium", + "18_TextBox_1": "https://training.slicer.org/", + "19_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n\nChan Zuckerberg Initiative (CZI)", + "6_TextBox_0": "El panel del módulo de bienvenida\ncontiene accesos directos para\ncargar diferentes tipos de datos.\nTambién hay disponibles datos de muestra.\n\nPulse sobre \"Descargar datos de muestra\" para\nacceder al módulo de datos de muestra.\t", + "7_Sampledata_title": "Datos de muestra", + "8_Sampledata_title": "Datos de muestra", + "7_TextBox_0": "El módulo Datos de muestra contiene\nenlaces a diferentes conjuntos de datos\nde muestra que pueden descargarse\nen Slicer.\t", + "8_ArrowText_0": "Pulse\ten\tMRHead para\tdescargar\tel\t\ndataset\ten\tSlicer.\t", + "14_MRBrainSampleDataset_title": "Dataset de Muestra del Cerebro MR", + "15_MRBrainSampleDataset_title": "Dataset de Muestra del Cerebro MR", + "16_MRBrainSampleDataset_title": "Dataset de Muestra del Cerebro MR", + "10_ArrowText_0": "Posicionar el ratón en el pin pequeño\t\nicono\ten la cima izquierda de esquina del visor rojo para exhibir el menú del visor", + "12_MRBrainSampleDataset_title": "Pulse en el icono de enlace para vincular los tres\nvisores 2D y en el icono del ojo que se encuentra\njunto a él para mostrar los cortes en el visor 3D. );", + "12_TextBox_0": "Los cortes axial, coronal y sagital\naparecen en el visor 3D. Vuelva al\nmódulo de bienvenida usando la\nflecha verde de la barra de herramientas );", + "13_GoingFurther_title": "Los cortes axial, coronal y sagital\naparecen en el visor 3D. Vuelva al\nmódulo de bienvenida usando la\nflecha verde de la barra de herramientas );", + "19_TextBox_0": "Agradecimientos", + "14_TextBox_1": "Alianza Nacional para Cómputo de Imagen Médcia\nNIH U54EB005148\n\nCentro de Análisis Neuroimagen\nNIH P41EB015902" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_fr.json b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_fr.json new file mode 100644 index 00000000..2e64122e --- /dev/null +++ b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_fr.json @@ -0,0 +1,65 @@ +{ + "0_TextBox_0": "Bienvenue dans Slicer", + "1_TextBox_0": "Bienvenue dans Slicer", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "1_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_2": "28/08/2024", + "0_TextBox_3": "Assistant Professor of Radiology\nBrigham and Women’s Hospital\nHarvard Medical School\n", + "2_Goal_title": "Objectif", + "1_Goal_body": "Ce tutoriel est une brève introduction au module Welcome du logiciel open-source Slicer. ", + "2_3DSlicerversion48_title": "3D Slicer version 4.8", + "6_WelcometoSlicer_title": "Bienvenue dans Slicer", + "3_TextBox_0": "Slicer5 Basics", + "7_SlicerUserInterface_title": "Interface utilisateur de Slicer", + "4_TextBox_1": "3D Slicer 5 version 5.10.0 includes over 100 modules and more than 190 extensions for image segmentation, registration and 3D visualization of medical imaging data.", + "7_ArrowText_0": "Barre d’outils", + "7_TextBox_1": "Visionneuse 3D", + "7_ArrowText_6": "Visionneuses anatomiques 2D", + "7_TextBox_5": "Sonde de données", + "1_TextBox_3": "Assistant Professor of Radiology\n\nBrigham and Women’s Hospital\n\nHarvard Medical School\n", + "2_Goal_body": "This tutorial is a short introduction to the Welcome module of the Slicer open-source software.", + "4_TextBox_0": "Slicer5 Basics", + "3_TextBox_1": "*Slicer is an open-source software for segmentation, registration and visualization of medical imaging data.\n*The platform is developed through a multi-institution effort of several NIH funded large-scale consortia.\n*Slicer is for medical research only, and is not FDA approved. ", + "5_TextBox_0": "L’onglet Documentation & Tutoriels \ncontient des liens vers \nle compendium de formation et les pages de documentation de la version 4.8 de 3D Slicer.\t", + "5_TextBox_1": "*Slicer is a multi-platform software developed and maintained on Mac OSX, Linux and Windows.\n\n*Slicer requires a minimum of 2 GB of RAM and a dedicated graphic accelerator with 64 MB of on-board graphic memory. ", + "6_TextBox_1": "Each module of Slicer includes a series of tabs, which give access to different functionalities.\n\nClick on the arrow symbol to display the content of each tab. ", + "7_TextBox_3": "User Interface (UI) panel of the Slicer Welcome Module", + "8_WelcomeModule_title": "Module Welcome", + "9_WelcomeModule_title": "Module Welcome", + "13_WelcomeModule_title": "Module Welcome", + "8_TextBox_1": "The Documentation & Tutorials tab contains links to the training compendium and documentation pages of 3D Slicer.", + "9_TextBox_0": "Le scan IRM du cerveau apparaît dans les visionneuses 2D.", + "10_SampleData_title": "Sample Data", + "11_SampleData_title": "Sample Data", + "12_SampleData_title": "Sample Data", + "10_TextBox_1": "The Sample Data module contains links to different sample datasets that can be downloaded into Slicer.", + "11_TextBox_0": "Cliquez sur l’icône de lien pour relier les trois visionneuses 2D, puis sur l’icône en forme d’œil à côté pour afficher les coupes dans la visionneuse 3D\t) ;", + "11_TextBox_1": "Chest CT", + "11_TextBox_2": "Cardiac CT", + "11_TextBox_3": "Diffusion Tensor Imaging (DTI) Dataset", + "11_TextBox_4": "Brain MRI (tumor patient)", + "12_ArrowText_0": "Click on MRHead to download the\ndataset in Slicer.", + "13_TextBox_0": "Pour en savoir plus sur Slicer et ses différentes fonctionnalités, consultez le compendium de Slicer 4.8.", + "14_TextBox_0": "Position the mouse on the little pin icon in the top left corner of the red viewer to display the viewer menu", + "15_TextBox_1": "Click on the link icon to link all three 2D viewers, and on the eye icon next to it\nto display the slices in the 3D viewer", + "16_TextBox_0": "The axial, coronal and sagittal slices appear in the 3D viewer.\nGo back to the Welcome module using the green arrow in the toolbar", + "17_GoingFurther_title": "Going Further", + "18_TextBox_0": "Going Further", + "17_TextBox_0": "To learn more about Slicer and its different functionalities, visit the Slicer Compendium", + "18_TextBox_1": "https://training.slicer.org/", + "19_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n\nChan Zuckerberg Initiative (CZI)", + "6_TextBox_0": "Le panneau du module Welcome contient des raccourcis pour charger différents types de données. Une série de données d’exemple est également disponible.\n\nCliquez sur Download Sample Data pour accéder au module Sample Data.\t", + "7_Sampledata_title": "Données d’exemple", + "8_Sampledata_title": "Données d’exemple", + "7_TextBox_0": "Le module Sample Data contient des liens vers différents ensembles de données d’exemple pouvant être téléchargés dans Slicer\t", + "8_ArrowText_0": "Cliquez sur MRHead pour télécharger l’ensemble de données dans Slicer\t", + "14_MRBrainSampleDataset_title": "Jeu de données d’exemple IRM du cerveau", + "15_MRBrainSampleDataset_title": "Jeu de données d’exemple IRM du cerveau", + "16_MRBrainSampleDataset_title": "Jeu de données d’exemple IRM du cerveau", + "10_ArrowText_0": "Placez la souris sur la petite icône en forme d’épingle dans le coin supérieur gauche de la visionneuse rouge pour afficher le menu de la visionneuse", + "12_MRBrainSampleDataset_title": "Cliquez sur l’icône de lien pour relier les trois visionneuses 2D, puis sur l’icône en forme d’œil à côté pour afficher les coupes dans la visionneuse 3D\t) ;", + "12_TextBox_0": "Les coupes axiale, coronale et sagittale apparaissent dans la visionneuse 3D.\nRetournez au module Welcome en utilisant la flèche verte dans la barre d’outils\t) ;", + "13_GoingFurther_title": "Les coupes axiale, coronale et sagittale apparaissent dans la visionneuse 3D.\nRetournez au module Welcome en utilisant la flèche verte dans la barre d’outils\t) ;", + "19_TextBox_0": "Remerciements", + "14_TextBox_1": "Alliance nationale pour l’informatique de l’imagerie médicale\nNIH U54EB005148\n\nCentre d’analyse neuroimagerie\nNIH P41EB015902" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_pt-BR.json b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_pt-BR.json new file mode 100644 index 00000000..f49de4ea --- /dev/null +++ b/Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_pt-BR.json @@ -0,0 +1,52 @@ +{ + "0_TextBox_0": "Bem-vindo ao Slicer", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_3": "Assistant Professor of Radiology\nBrigham and Women’s Hospital\nHarvard Medical School\n", + "1_TextBox_0": "Slicer Welcome", + "1_TextBox_1": "Sonia Pujol, Ph.D.", + "1_TextBox_3": "Assistant Professor of Radiology\n\nBrigham and Women’s Hospital\n\nHarvard Medical School\n", + "2_Goal_title": "Goal", + "2_Goal_body": "This tutorial is a short introduction to the Welcome module of the Slicer open-source software.", + "3_TextBox_0": "Slicer5 Basics", + "3_TextBox_1": "*Slicer is an open-source software for segmentation, registration and visualization of medical imaging data.\n*The platform is developed through a multi-institution effort of several NIH funded large-scale consortia.\n*Slicer is for medical research only, and is not FDA approved. ", + "4_TextBox_0": "Slicer5 Basics", + "4_TextBox_1": "3D Slicer 5 version 5.10.0 includes over 100 modules and more than 190 extensions for image segmentation, registration and 3D visualization of medical imaging data.", + "5_TextBox_0": "Supported Platforms", + "5_TextBox_1": "*Slicer is a multi-platform software developed and maintained on Mac OSX, Linux and Windows.\n\n*Slicer requires a minimum of 2 GB of RAM and a dedicated graphic accelerator with 64 MB of on-board graphic memory. ", + "6_WelcometoSlicer_title": "Welcome to Slicer", + "6_TextBox_1": "Each module of Slicer includes a series of tabs, which give access to different functionalities.\n\nClick on the arrow symbol to display the content of each tab. ", + "7_SlicerUserInterface_title": "Slicer User Interface", + "7_ArrowText_0": "Toolbar", + "7_TextBox_1": "3D viewer", + "7_TextBox_3": "User Interface (UI) panel of the Slicer Welcome Module", + "7_TextBox_5": "Data probe", + "7_ArrowText_6": "2D anatomical viewers", + "8_WelcomeModule_title": "Welcome Module", + "8_TextBox_1": "The Documentation & Tutorials tab contains links to the training compendium and documentation pages of 3D Slicer.", + "9_WelcomeModule_title": "Welcome Module", + "9_TextBox_0": "The Welcome module panel contains shortcuts for loading different types of data. A series of sample data are also available.\n\nClick on Download Sample Data to access the Sample Data Module", + "10_SampleData_title": "Sample Data", + "10_TextBox_1": "The Sample Data module contains links to different sample datasets that can be downloaded into Slicer.", + "11_SampleData_title": "Sample Data", + "11_TextBox_0": "Brain MR", + "11_TextBox_1": "Chest CT", + "11_TextBox_2": "Cardiac CT", + "11_TextBox_3": "Diffusion Tensor Imaging (DTI) Dataset", + "11_TextBox_4": "Brain MRI (tumor patient)", + "12_SampleData_title": "Sample Data", + "12_ArrowText_0": "Click on MRHead to download the\ndataset in Slicer.", + "13_WelcomeModule_title": "Welcome Module", + "13_TextBox_0": "The MR scan of the brain appears\nin the 2D viewers.", + "14_MRBrainSampleDataset_title": "MR Brain Sample Dataset", + "14_TextBox_0": "Position the mouse on the little pin icon in the top left corner of the red viewer to display the viewer menu", + "15_MRBrainSampleDataset_title": "MR Brain Sample Dataset", + "15_TextBox_1": "Click on the link icon to link all three 2D viewers, and on the eye icon next to it\nto display the slices in the 3D viewer", + "16_MRBrainSampleDataset_title": "MR Brain Sample Dataset", + "16_TextBox_0": "The axial, coronal and sagittal slices appear in the 3D viewer.\nGo back to the Welcome module using the green arrow in the toolbar", + "17_GoingFurther_title": "Going Further", + "17_TextBox_0": "To learn more about Slicer and its different functionalities, visit the Slicer Compendium", + "18_TextBox_0": "Going Further", + "18_TextBox_1": "https://training.slicer.org/", + "19_TextBox_0": "Acknowledgements", + "19_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n\nChan Zuckerberg Initiative (CZI)" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_en.json b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_en.json new file mode 100644 index 00000000..42c07552 --- /dev/null +++ b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_en.json @@ -0,0 +1,39 @@ +{ + "0_TextBox_0": "Slicer4 Minute\n", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_3": "Assistant Professor of Radiology\nBrigham and Women’s Hospital\nHarvard Medical School", + "1_TextBox_0": "Slicer4 minute tutorial", + "16_TextBox_0": "Slicer4 minute tutorial", + "1_TextBox_1": "This tutorial is a 4-minute introduction to the 3D visualization capabilities of the Slicer5 software for medical image analysis. ", + "2_TextBox_0": "Slicer5 software & dataset", + "2_TextBox_1": "*Download the Slicer5 software available at http://download.slicer.org\n\n*Download the Slicer4minute dataset available at https://www.slicer.org/wiki/Documentation/4.10/Training", + "3_3DSlicerversion5_title": "3D Slicer version 5", + "4_TextBox_0": "3D Slicer Scene", + "4_TextBox_1": "*A Slicer scene is a MRML (Medical Reality Modeling Language) file that contains a list of elements loaded into Slicer (volumes, models, fiducials, transforms, etc.)\n*In the following example, we use a scene 'Slicer4minute.mrml' composed of an MRI scan and 3D models of the head. \n*The scene file and datasets have been saved as a MRB (Medical Reality Bundle) file. \n*The MRB file format is Slicer's archive file format.", + "5_LoadingtheSlicer4minutedataset_title": "Loading the Slicer4minute dataset", + "5_TextBox_1": "Drag and drop the slicer4minute.mrb to load the scene in Slicer", + "6_Slicer4minuteScene_title": "Slicer4minute Scene", + "6_TextBox_1": "Slicer displays the elements of the slicer4minute scene. The scene contains and MRI scan and 3D surface models of the brain.", + "7_TextBox_0": "Select the module Models", + "8_3Dvisualization_title": "3D visualization", + "8_TextBox_0": "Click on the pin icon on the top left corner of the red slice to display the slice viewer menu.\nClick on the eye icon to display the axial slice in the 3D viewer", + "9_TextBox_1": "Use the slider of the red viewer to browse through the axial MR slices. \n\nSlicer simultaneously displays the axial slice in the 3D viewer", + "10_TextBox_0": "Select the Skin model and lower its opacity using the Opacity slider in the 3D Display tab", + "10_TextBox_1": "The skull_bone.vtk model appears through the skin.", + "11_TextBox_0": "Position the mouse in the 3D viewer, click on the left-mouse button to drag and rotate the model. \nClick on the right-mouse button to zoom in and out", + "12_AnatomicalViews_title": "Anatomical Views", + "12_TextBox_0": "Click on the pin icons in the top left corner of the red and green viewer to display the slice viewer menu\n\nClick on the eye icon to display the axial and coronal slice in the 3D viewer", + "13_TextBox_0": "Turn off the visibility of the skull to display the brain white matter model", + "14_TextBox_0": "The white matter surface, as well as the left and right optic nerves, appear in the viewer", + "15_TextBox_0": "Select the hemispheric_white_matter.vtk model\n\nCheck Clipping in the 3D Display tab\n\nIn the Clipping Planes tab, select the option 'Green Slice Clipping' and check 'Negative'", + "16_TextBox_1": "*This tutorial was a short introduction on interactive 3D visualization of MRI data and 3D models in Slicer.\n\n*The Slicer5 training compendium contains a series of tutorials and pre-computed datasets to learn how to use the software.", + "17_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n", + "7_3DVisualization_title": "3D Visualization", + "9_3DVisualization_title": "3D Visualization", + "10_3DVisualization_title": "3D Visualization", + "11_3DVisualization_title": "3D Visualization", + "13_3DVisualization_title": "3D Visualization", + "14_3DVisualization_title": "3D Visualization", + "15_3DVisualization_title": "3D Visualization", + "17_TextBox_0": "Acknowledgements" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_es.json b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_es.json new file mode 100644 index 00000000..e2a70141 --- /dev/null +++ b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_es.json @@ -0,0 +1,51 @@ +{ + "0_TextBox_0": "Slicer4 Minute\n", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_2": "Profesor\tAdjunto\tde\tRadiología\nHospital\tBrigham\tand\tWomen's\nFacultad\tde\tMedicina\tde\tHarvard\t", + "1_Slicer4minutetutorial_title": "Tutorial de Slicer4 minutos\t);", + "1_Slicer4minutetutorial_body": "Tutorial de Slicer4 minutos\t);", + "2_3DSlicerversion48_title": "3D Slicer versión 4.8\t", + "3_3DSlicerversion48_title": "3D Slicer versión 4.8", + "3_TextBox_0": "Arrastre y suelte el archivo\nslicer4minute.mrb para\ncargar la escena en Slicer", + "0_TextBox_3": "Assistant Professor of Radiology\nBrigham and Women’s Hospital\nHarvard Medical School", + "1_TextBox_0": "Slicer4 minute tutorial", + "16_TextBox_0": "Slicer4 minute tutorial", + "1_TextBox_1": "This tutorial is a 4-minute introduction to the 3D visualization capabilities of the Slicer5 software for medical image analysis. ", + "2_TextBox_0": "Slicer5 software & dataset", + "2_TextBox_1": "*Download the Slicer5 software available at http://download.slicer.org\n\n*Download the Slicer4minute dataset available at https://www.slicer.org/wiki/Documentation/4.10/Training", + "3_3DSlicerversion5_title": "3D Slicer version 5", + "4_TextBox_0": "Slicer muestra los elementos\nde la escena de slicer4minute.\nLa escena contiene una resonancia\nmagnética y modelos de superficie\n3D del cerebro.\t", + "4_TextBox_1": "*A Slicer scene is a MRML (Medical Reality Modeling Language) file that contains a list of elements loaded into Slicer (volumes, models, fiducials, transforms, etc.)\n*In the following example, we use a scene 'Slicer4minute.mrml' composed of an MRI scan and 3D models of the head. \n*The scene file and datasets have been saved as a MRB (Medical Reality Bundle) file. \n*The MRB file format is Slicer's archive file format.", + "5_LoadingtheSlicer4minutedataset_title": "Loading the Slicer4minute dataset", + "5_TextBox_1": "Drag and drop the slicer4minute.mrb to load the scene in Slicer", + "6_Slicer4minuteScene_title": "Escena Slicer4minute", + "6_TextBox_1": "Pulse en el icono del alfiler en la esquina superior izquierda del corte rojo\npara abrir el menú del visor de cortes.\nPulse en el icono del ojo para ver el corte axial en el visor 3D", + "7_TextBox_0": "Select the module Models", + "8_3Dvisualization_title": "3D visualization", + "8_TextBox_0": "Click on the pin icon on the top left corner of the red slice to display the slice viewer menu.\nClick on the eye icon to display the axial slice in the 3D viewer", + "9_TextBox_1": "Use the slider of the red viewer to browse through the axial MR slices. \n\nSlicer simultaneously displays the axial slice in the 3D viewer", + "10_TextBox_0": "Pulse en los iconos de alfiler en\nla esquina superior izquierda del\nvisor rojo y verde para abrir el\nmenú del visor de cortes.\n\nPulse en el icono del ojo para mostrar los\ncortes axial y coronal en el visor 3D", + "10_TextBox_1": "The skull_bone.vtk model appears through the skin.", + "11_TextBox_0": "Apaga\tla\tvisibilidad\tdel\tcráneo\npara\texhibir\tel\tcerebro\ten\nmodo\tmapa\tblanco", + "12_AnatomicalViews_title": "Anatomical Views", + "12_TextBox_0": "Click on the pin icons in the top left corner of the red and green viewer to display the slice viewer menu\n\nClick on the eye icon to display the axial and coronal slice in the 3D viewer", + "13_TextBox_0": "Turn off the visibility of the skull to display the brain white matter model", + "14_TextBox_0": "The white matter surface, as well as the left and right optic nerves, appear in the viewer", + "15_TextBox_0": "Select the hemispheric_white_matter.vtk model\n\nCheck Clipping in the 3D Display tab\n\nIn the Clipping Planes tab, select the option 'Green Slice Clipping' and check 'Negative'", + "16_TextBox_1": "*This tutorial was a short introduction on interactive 3D visualization of MRI data and 3D models in Slicer.\n\n*The Slicer5 training compendium contains a series of tutorials and pre-computed datasets to learn how to use the software.", + "17_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n", + "7_3DVisualization_title": "Visualización 3D", + "9_3DVisualization_title": "Visualización 3D", + "10_3DVisualization_title": "Visualización 3D", + "11_3DVisualization_title": "Visualización 3D", + "13_3DVisualization_title": "Visualización 3D", + "14_3DVisualization_title": "Visualización 3D", + "15_3DVisualization_title": "Visualización 3D", + "5_TextBox_0": "Selecciona el módulo Modelos\t", + "6_ArrowText_0": "Conmutar la visibilidad de los cortes en la vista 3D", + "9_TextBox_0": "Coloque el ratón en el visor 3D y pulse con el botón izquierdo para arrastrar y rotar el modelo.\nPulse con el botón derecho para acercar o alejar la imagen", + "10_Anatomicalviews_title": "Vistas anatómicas", + "12_TextBox_3": "Seleccione\tel\tmodelo\themispheric_white\tmatter.vtk\n\nMarque\tla\topción\tRecorte\ten\tla\tpestaña\tVisualización\t3D.\n\nEn\tla\tpestaña\tPlanos\tde\tRecorte,\tseleccione\tla\topción\t\"Recorte\tde\tCorte\tVerde\"\ty\tmarque\t\"Negativo\"", + "17_TextBox_0": "Agradecimientos", + "13_TextBox_1": "Alianza Nacional para la Computación de Imágenes Médicas\nNIH U54EB005149\n\nCentro de Análisis de Neuroimágenes\nNIH P41EB015902\n\nIniciativa Chan Zuckerberg\nSubvención de Código Abierto Esencial para la Ciencia n.° 2022-252572 (5022)" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_fr.json b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_fr.json new file mode 100644 index 00000000..ab9130ee --- /dev/null +++ b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_fr.json @@ -0,0 +1,52 @@ +{ + "0_TextBox_0": "Slicer4 Minute\n", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_2": "Professeure adjointe de radiologie\nBrigham and Women’s Hospital\nHarvard Medical School\t", + "1_Slicer4minutetutorial_title": "Tutoriel Slicer4 minute \t);", + "1_Slicer4minutetutorial_body": "Tutoriel Slicer4 minute \t);", + "2_3DSlicerversion48_title": "3D Slicer version 4.8\t", + "3_3DSlicerversion48_title": "3D Slicer version 4.8", + "3_TextBox_0": "Glissez-déposez le fichier slicer4minute.mrb pour charger la scène dans Slicer.", + "0_TextBox_3": "Assistant Professor of Radiology\nBrigham and Women’s Hospital\nHarvard Medical School", + "1_TextBox_0": "Slicer4 minute tutorial", + "16_TextBox_0": "Slicer4 minute tutorial", + "1_TextBox_1": "This tutorial is a 4-minute introduction to the 3D visualization capabilities of the Slicer5 software for medical image analysis. ", + "2_TextBox_0": "Slicer5 software & dataset", + "2_TextBox_1": "*Download the Slicer5 software available at http://download.slicer.org\n\n*Download the Slicer4minute dataset available at https://www.slicer.org/wiki/Documentation/4.10/Training", + "3_3DSlicerversion5_title": "3D Slicer version 5", + "4_TextBox_0": "Slicer affiche les éléments de la scène slicer4minute.\nLa scène contient une IRM ainsi que des modèles de surface 3D du cerveau.\t", + "4_TextBox_1": "*A Slicer scene is a MRML (Medical Reality Modeling Language) file that contains a list of elements loaded into Slicer (volumes, models, fiducials, transforms, etc.)\n*In the following example, we use a scene 'Slicer4minute.mrml' composed of an MRI scan and 3D models of the head. \n*The scene file and datasets have been saved as a MRB (Medical Reality Bundle) file. \n*The MRB file format is Slicer's archive file format.", + "5_LoadingtheSlicer4minutedataset_title": "Loading the Slicer4minute dataset", + "5_TextBox_1": "Drag and drop the slicer4minute.mrb to load the scene in Slicer", + "6_Slicer4minuteScene_title": "Scène Slicer4minute", + "6_TextBox_1": "Cliquez sur l’icône en forme d’épingle dans le coin supérieur gauche de la coupe rouge pour afficher le menu de la visionneuse de coupes\nCliquez sur l’icône en forme d’œil pour afficher la coupe axiale dans la Visionneuse 3D", + "7_TextBox_0": "Utilisez le curseur de la visionneuse rouge pour parcourir les coupes axiales de l’IRM\nSlicer affiche simultanément la coupe axiale dans la visionneuse 3D\t", + "8_3Dvisualization_title": "3D visualization", + "8_TextBox_0": "Sélectionnez le modèle Skin et réduisez son opacité en utilisant le curseur Opacity dans l’onglet 3D Display\t", + "9_TextBox_1": "Use the slider of the red viewer to browse through the axial MR slices. \n\nSlicer simultaneously displays the axial slice in the 3D viewer", + "10_TextBox_0": "Cliquez sur les icônes en forme d’épingle dans le coin supérieur gauche des visionneuses rouge et verte pour afficher le menu de la visionneuse de coupes\n\nCliquez sur l’icône en forme d’œil pour afficher les coupes axiale et coronale dans la visionneuse 3D", + "10_TextBox_1": "The skull_bone.vtk model appears through the skin.", + "11_TextBox_0": "Désactivez la visibilité du crâne pour afficher le cerveau en mode maPer blanche", + "12_AnatomicalViews_title": "Anatomical Views", + "12_TextBox_0": "Click on the pin icons in the top left corner of the red and green viewer to display the slice viewer menu\n\nClick on the eye icon to display the axial and coronal slice in the 3D viewer", + "13_TextBox_0": "Turn off the visibility of the skull to display the brain white matter model", + "14_TextBox_0": "The white matter surface, as well as the left and right optic nerves, appear in the viewer", + "15_TextBox_0": "Select the hemispheric_white_matter.vtk model\n\nCheck Clipping in the 3D Display tab\n\nIn the Clipping Planes tab, select the option 'Green Slice Clipping' and check 'Negative'", + "16_TextBox_1": "*This tutorial was a short introduction on interactive 3D visualization of MRI data and 3D models in Slicer.\n\n*The Slicer5 training compendium contains a series of tutorials and pre-computed datasets to learn how to use the software.", + "17_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n", + "7_3DVisualization_title": "Visualisation 3D", + "9_3DVisualization_title": "Visualisation 3D", + "10_3DVisualization_title": "Visualisation 3D", + "11_3DVisualization_title": "Visualisation 3D", + "13_3DVisualization_title": "Visualisation 3D", + "14_3DVisualization_title": "Visualisation 3D", + "15_3DVisualization_title": "Visualisation 3D", + "5_TextBox_0": "Sélectionnez le module Models\t", + "6_ArrowText_0": "Basculer la visibilité des coupes dans la vue 3D", + "8_TextBox_1": "Le modèle skull_bone.vtk apparaît à travers la peau\t", + "9_TextBox_0": "Placez la souris dans la visionneuse 3D, cliquez sur le bouton gauche de la souris pour déplacer et faire pivoter le modèle\nCliquez sur le bouton droit de la souris pour zoomer avant et arrière", + "10_Anatomicalviews_title": "Vues anatomiques", + "12_TextBox_3": "Sélectionnez le modèle hemispheric_white matter.vtk\n\nCochez Clipping dans l’onglet 3D Display\n\nDans l’onglet Clipping Planes, sélectionnez l’option Green Slice Clipping et cochez Negative", + "17_TextBox_0": "Remerciements", + "13_TextBox_1": "National Alliance for Medical Imaging Computing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n\nChan Zuckerberg Initiative\nEssential Open Source for Science Grant #2022-252572 (5022)" +} \ No newline at end of file diff --git a/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_pt-BR.json b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_pt-BR.json new file mode 100644 index 00000000..06be81b1 --- /dev/null +++ b/Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_pt-BR.json @@ -0,0 +1,39 @@ +{ + "0_TextBox_0": "Slicer4 Minute\n", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_3": "Assistant Professor of Radiology\nBrigham and Women’s Hospital\nHarvard Medical School", + "1_TextBox_0": "Slicer4 minute tutorial", + "1_TextBox_1": "This tutorial is a 4-minute introduction to the 3D visualization capabilities of the Slicer5 software for medical image analysis. ", + "2_TextBox_0": "Slicer5 software & dataset", + "2_TextBox_1": "*Download the Slicer5 software available at http://download.slicer.org\n\n*Download the Slicer4minute dataset available at https://www.slicer.org/wiki/Documentation/4.10/Training", + "3_3DSlicerversion5_title": "3D Slicer version 5", + "4_TextBox_0": "3D Slicer Scene", + "4_TextBox_1": "*A Slicer scene is a MRML (Medical Reality Modeling Language) file that contains a list of elements loaded into Slicer (volumes, models, fiducials, transforms, etc.)\n*In the following example, we use a scene 'Slicer4minute.mrml' composed of an MRI scan and 3D models of the head. \n*The scene file and datasets have been saved as a MRB (Medical Reality Bundle) file. \n*The MRB file format is Slicer's archive file format.", + "5_LoadingtheSlicer4minutedataset_title": "Loading the Slicer4minute dataset", + "5_TextBox_1": "Drag and drop the slicer4minute.mrb to load the scene in Slicer", + "6_Slicer4minuteScene_title": "Slicer4minute Scene", + "6_TextBox_1": "Slicer displays the elements of the slicer4minute scene. The scene contains and MRI scan and 3D surface models of the brain.", + "7_3DVisualization_title": "3D Visualization", + "7_TextBox_0": "Select the module Models", + "8_3Dvisualization_title": "3D visualization", + "8_TextBox_0": "Click on the pin icon on the top left corner of the red slice to display the slice viewer menu.\nClick on the eye icon to display the axial slice in the 3D viewer", + "9_3DVisualization_title": "3D Visualization", + "9_TextBox_1": "Use the slider of the red viewer to browse through the axial MR slices. \n\nSlicer simultaneously displays the axial slice in the 3D viewer", + "10_3DVisualization_title": "3D Visualization", + "10_TextBox_0": "Select the Skin model and lower its opacity using the Opacity slider in the 3D Display tab", + "10_TextBox_1": "The skull_bone.vtk model appears through the skin.", + "11_3DVisualization_title": "3D Visualization", + "11_TextBox_0": "Position the mouse in the 3D viewer, click on the left-mouse button to drag and rotate the model. \nClick on the right-mouse button to zoom in and out", + "12_AnatomicalViews_title": "Anatomical Views", + "12_TextBox_0": "Click on the pin icons in the top left corner of the red and green viewer to display the slice viewer menu\n\nClick on the eye icon to display the axial and coronal slice in the 3D viewer", + "13_3DVisualization_title": "3D Visualization", + "13_TextBox_0": "Turn off the visibility of the skull to display the brain white matter model", + "14_3DVisualization_title": "3D Visualization", + "14_TextBox_0": "The white matter surface, as well as the left and right optic nerves, appear in the viewer", + "15_3DVisualization_title": "3D Visualization", + "15_TextBox_0": "Select the hemispheric_white_matter.vtk model\n\nCheck Clipping in the 3D Display tab\n\nIn the Clipping Planes tab, select the option 'Green Slice Clipping' and check 'Negative'", + "16_TextBox_0": "Slicer4 minute tutorial", + "16_TextBox_1": "*This tutorial was a short introduction on interactive 3D visualization of MRI data and 3D models in Slicer.\n\n*The Slicer5 training compendium contains a series of tutorials and pre-computed datasets to learn how to use the software.", + "17_TextBox_0": "Acknowledgements", + "17_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n" +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ar-SA.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ar-SA.json new file mode 100644 index 00000000..119c0bd9 --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ar-SA.json @@ -0,0 +1,49 @@ +{ + "0_TextBox_0": "AI-based Segmentation in 3D Slicer", + "0_TextBox_1": "Sonia Pujol, Ph. D\nBrigham and Women's Hospital,\nHarvard Medical School\nBoston, MA", + "0_TextBox_3": "Slicer Ribeirão Preto Workshop\nJune 30, 2025", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_0": "Manual vs AI-powered Segmentation", + "1_TextBox_1": "Medical images have traditionally been manually segmented, which is a time-consuming process that requires intensive effort by radiologists and is subject to inter-reader variability.", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a Model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Workshop", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pretrained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_1": "Multiple modalities Support (CT, MRI).\n\n\nMultiple anatomies (head, thorax, abdomen, pelvis, etc.).\n\n\nMultiple pathologies (tumor, hemorrhage, edema).", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate.\n\n\nSegmentation Task #2: Brain Glioma.\n\n\nSegmentation Task #3: Whole Body Segmentation.", + "8_TextBox_0": "AI Segmentation Task #1: Prostate", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Click on Add Data in the Welcome to Slicer Module\n\nClick on Choose Directory to Add and browse to the location of the Slicer datasets", + "11_TextBox_0": "Slicer loads the prostate MRI data set", + "12_TextBox_0": "Click on Welcome to Slicer in the Modules' menu and browse to the category Segmentation\n\nSelec the MONAI Auto3DSeg module", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "Select the model Prostate - Multisequence", + "14_TextBox_0": "Enter the Input T2 volume msd-prostate-01-adc and the Input ADC volume msd-prostate-01-adc.", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "16_TextBox_0": "Slicer shows the results of the AI-based prostate segmentation", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer Module\n\nClick on Choose File(s) to Add and browse to the loccation of the Slicer datasets", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t12f\nInput T1C volume: BraTS-GLI_00005-00-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Appply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6: CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the IA-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D SlicerMONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible by two CZI Essential Open Source Software for Science (EOSS cycle 4 & 5) grants.", + "15_TextBox_0": "Slicer starts the inference", + "31_TextBox_0": "Acknowledgements" +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_en.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_en.json new file mode 100644 index 00000000..119c0bd9 --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_en.json @@ -0,0 +1,49 @@ +{ + "0_TextBox_0": "AI-based Segmentation in 3D Slicer", + "0_TextBox_1": "Sonia Pujol, Ph. D\nBrigham and Women's Hospital,\nHarvard Medical School\nBoston, MA", + "0_TextBox_3": "Slicer Ribeirão Preto Workshop\nJune 30, 2025", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_0": "Manual vs AI-powered Segmentation", + "1_TextBox_1": "Medical images have traditionally been manually segmented, which is a time-consuming process that requires intensive effort by radiologists and is subject to inter-reader variability.", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a Model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Workshop", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pretrained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_1": "Multiple modalities Support (CT, MRI).\n\n\nMultiple anatomies (head, thorax, abdomen, pelvis, etc.).\n\n\nMultiple pathologies (tumor, hemorrhage, edema).", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate.\n\n\nSegmentation Task #2: Brain Glioma.\n\n\nSegmentation Task #3: Whole Body Segmentation.", + "8_TextBox_0": "AI Segmentation Task #1: Prostate", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Click on Add Data in the Welcome to Slicer Module\n\nClick on Choose Directory to Add and browse to the location of the Slicer datasets", + "11_TextBox_0": "Slicer loads the prostate MRI data set", + "12_TextBox_0": "Click on Welcome to Slicer in the Modules' menu and browse to the category Segmentation\n\nSelec the MONAI Auto3DSeg module", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "Select the model Prostate - Multisequence", + "14_TextBox_0": "Enter the Input T2 volume msd-prostate-01-adc and the Input ADC volume msd-prostate-01-adc.", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "16_TextBox_0": "Slicer shows the results of the AI-based prostate segmentation", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer Module\n\nClick on Choose File(s) to Add and browse to the loccation of the Slicer datasets", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t12f\nInput T1C volume: BraTS-GLI_00005-00-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Appply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6: CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the IA-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D SlicerMONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible by two CZI Essential Open Source Software for Science (EOSS cycle 4 & 5) grants.", + "15_TextBox_0": "Slicer starts the inference", + "31_TextBox_0": "Acknowledgements" +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_es.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_es.json new file mode 100644 index 00000000..ae633758 --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_es.json @@ -0,0 +1,78 @@ +{ + "1_0_ArrowText_0": "Pulse sobre Añadir Datos en el Bienvenido\nen el módulo Slicer", + "2_2_TextBox_1": "Pulse en Elegir Directorio para añadir y\nexplorar el lugar de las bases de datos\nSlicer", + "3_0_TextBox_0": "Slicer carga el conjunto de datos de\nresonancia magnética de próstata", + "4_3_TextBox_1": "Pulse sobre Bienvenido a Rebanada en\nel menú de Módulos y examinar a la\n\ncategoría Segmentación.\n\nSeleccione el módulo\n MONAI Auto3DSeg", + "5_0_ArrowText_0": "Introduzca el nombre Próstata del modelo\nen el menú de modelo Segmentación", + "0_TextBox_0": "AIBasedSegmentationIn3DSlicer", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_3": "Segmentación basada en IA en 3D Slicer", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_0": "Slicer carga el conjunto de datos de resonancia magnética de próstata", + "1_TextBox_1": "Clic en Agregar datos en el módulo Bienvenido a \tSlicer", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a Model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Workshop", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pretrained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_1": "Clic en Crear nueva segmentación en\nAplicar", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate.\n\n\nSegmentation Task #2: Brain Glioma.\n\n\nSegmentation Task #3: Whole Body Segmentation.", + "8_TextBox_0": "Slicer muestra el resultado de la segmentación prostática basada en AI", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Selecciona el modelo Segmentación de Tumor Cerebral\n(BRATS) GLI", + "11_TextBox_0": "Ingrese los volúmenes de entrada de la siguiente manera:\nVolumen de entrada T2F: BraTS-GLI_00005-000-t12f\nVolumen de entrada T1C: BraTS-GLI_00005-000-t1c\nVolumen de entrada T1N: BraTS-GLI_00005-000-t1n\nVolumen de entrada T2W: BraTS-GLI_00005-000-t2w\nClic en Crear nueva segmentación al Aplicar\nClic en Aplicar para iniciar la segmentación", + "12_TextBox_0": "Slicer comienza a ejecutar la tarea de inferencia", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "Seleccione el modelo Próstata – Multisecuencia", + "14_TextBox_0": "En el añadir módulo de datos DICOM\nseleccione al Paciente paciente1 y\ndoble clic en la imagen\nCT_Torax_Abdomen para cargarlo en\nSlicer", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "16_TextBox_0": "Seleccionar el input Volumen 6: CT_Torax_Abdomen\nClic en Crear nueva Segmentación en Aplicar\nClic en Aplicar para iniciar la segmentación", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer Module\n\nClick on Choose File(s) to Add and browse to the loccation of the Slicer datasets", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t12f\nInput T1C volume: BraTS-GLI_00005-00-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Appply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6: CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the IA-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D SlicerMONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible by two CZI Essential Open Source Software for Science (EOSS cycle 4 & 5) grants.", + "7_0_TextBox_0": "Introduzca el volumen T2 de entrada\nmsd-prostate-01-adc e introduzca el\nvolumen ADC msd-prostate-01-adc", + "7_0_ArrowText_1": "Seleccione Crear segmentación nueva\nen Aplicar", + "7_0_ArrowText_2": "Pulse sobre Aplicar", + "8_0_TextBox_0": "El rebanador inicia la inferencia", + "9_0_TextBox_0": "El rebanador muestra el resultado del\nIA-basada en segmentación de próstata", + "10_2_TextBox_2": "Pulse en Añadir Datos en el módulo\nBienvenido al módulo Rebanador\n\n\n\n\n\n\n\n\n\n\nPulse sobre Elegir Archivo(s) para Añadir y\nexaminar al lugar del conjunto de datos de\nla base de datos Rebanador", + "0_TextBox_2": "30/06/2025", + "3_ArrowText_0": "Clic en Bienvenido a Slicer en el\nMenú de módulos y navegar a\n la categoría Segmentación.", + "4_ArrowText_0": "Ingrese el nombre del modelo Próstata en\nel menú del modelo de segmentación", + "5_ArrowText_0": "Ingresar el volumen de entrada T2 msdprostate-01-adc", + "6_ArrowText_0": "Y el volumen ADC de entrada msd-prostate-01-adc", + "15_TextBox_0": "Slicer inicia la inferencia", + "9_TextBox_0": "Cargar dataset4_BrainMRI_Glioma", + "10_ArrowText_0": "Seleccione el módulo MONAIAuto3DSeg e introduzca\nel nombre de modelo Segmentación de Tumor Cerebral\nen el menú del modelo Segmentación", + "13_ArrowText_1": "Una vez que la segmentación esté hecha, 'Procesamiento terminado'\naparece en el IGU Slicer", + "15_ArrowText_0": "Seleccionar el módulo MONAIAAuto3DSeg y entrar el\nnombre del modelo Segmentación de Cuerpo Completo en el\nmenú de modelo de Segmentación);", + "15_ArrowText_1": "Seleccionar el módulo MONAIAAuto3DSeg y entrar el\nnombre del modelo Segmentación de Cuerpo Completo en el\nmenú de modelo de Segmentación);", + "18_TextBox_0": "Slicer exhibe los resultados de la segmentación basada en IA\nusando la Segmentación de Cuerpo Completo TS1- rápida", + "31_TextBox_0": "Agradecimientos", + "13_0_TextBox_0": "Introduzca los volúmenes de entrada como sigue:", + "16_2_TextBox_0": "En el módulo Añadir Datos DICOM,\nselecciona el Paciente paciente1 y\npulsa en Cargar para cargarlo en el\nRebanador", + "17_0_TextBox_0": "Seleccione el módulo MONAIAuto3DSeg e introduzca\nel nombre del modelo Segmentación de Cuerpo Completo\n\nen el menú Segmentación del modelo", + "17_0_ArrowText_1": "Seleccione el modelo Segmentación de Cuerpo Completo\nTS1 - rápido", + "18_0_TextBox_3": "Seleccione la entrada del Volumen 6: TC_Tórax_Abdomen.\n\nPulse en Crear segmentación nueva sobre Aplicar\nPulse en Aplicar para iniciar la segmentación", + "19_0_TextBox_0": "Rebanador comienza la segmentación", + "20_0_TextBox_1": "Pulse sobre Mostrar 2D para\n\nver el segmento en vista 3D" +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_fr.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_fr.json new file mode 100644 index 00000000..c4a8dbfa --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_fr.json @@ -0,0 +1,78 @@ +{ + "1_0_ArrowText_0": "Cliquez sur Ajouter des données dans le module Bienvenue \ndans Slicer", + "2_2_TextBox_1": "Cliquez sur Choisir un répertoire pour ajouter\net naviguez jusqu'à l'emplacement des\njeux de données Slicer", + "3_0_TextBox_0": "Slicer charge l'IRM de la prostate\nbase de données", + "4_3_TextBox_1": "Cliquez sur Bienvenue dans Slicer dans le\nmenu Modules et naviguez jusqu'à\n\nla catégorie Segmentation.\n\nSélectionnez le module MONAI Auto3DSeg", + "5_0_ArrowText_0": "Saisissez le nom du modèle Prostate dans\n le menu Modèle de segmentation", + "0_TextBox_0": "AIBasedSegmentationIn3DSlicer", + "0_TextBox_1": "Sonia Pujol, Ph.D.", + "0_TextBox_3": "Segmentation basée sur l'IA dans 3D Slicer", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_0": "Slicer charge l'ensemble de données IRM de la prostate", + "1_TextBox_1": "Cliquez sur Add Data dans le module Welcome to Slicer", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a Model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Workshop", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pretrained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_1": "Cliquez sur Create new segmentation sur Apply", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate.\n\n\nSegmentation Task #2: Brain Glioma.\n\n\nSegmentation Task #3: Whole Body Segmentation.", + "8_TextBox_0": "Slicer affiche le résultat de la segmentation de la prostate basée sur l’IA", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Sélectionner le modèle Brain Tumor Segmentation\n(BRATS) GLI", + "11_TextBox_0": "Saisissez les volumes d’entrée comme suit :\nVolume T2F d’entrée : BraTS-GLI_00005-000-t12f\nVolume T1C d’entrée : BraTS-GLI_00005-000-t1c\nVolume T1N d’entrée : BraTS-GLI_00005-000-t1n\nVolume T2W d’entrée : BraTS-GLI_00005-000-t2w\nCliquez sur Create new Segmentation dans Apply\nCliquez sur Apply pour démarrer la segmentation", + "12_TextBox_0": "Slicer commence l’exécution de la tâche d’inférence", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "Sélectionner le modèle Prostate - Multiséquence", + "14_TextBox_0": "Dans le module Add DICOM Data, sélectionnez le patient patient1 et double-cliquez sur l’image CT_Thorax_Abdomen pour la charger dans Slicer", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "16_TextBox_0": "Sélectionnez le volume d’entrée 6 : CT_Thorax_Abdomen\nCliquez sur Create new Segmentation dans Apply \nCliquez sur Apply pour démarrer la segmentation", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer Module\n\nClick on Choose File(s) to Add and browse to the loccation of the Slicer datasets", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t12f\nInput T1C volume: BraTS-GLI_00005-00-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Appply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6: CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the IA-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D SlicerMONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible by two CZI Essential Open Source Software for Science (EOSS cycle 4 & 5) grants.", + "7_0_TextBox_0": "Entrez le volume T2 d'entrée msd-\nprostate-01-adc et le volume ADC \nd'entrée msd-prostate-01-adc", + "7_0_ArrowText_1": "Sélectionner Créer une nouvelle segmentation sur\nAppliquer", + "7_0_ArrowText_2": "Cliquez sur Appliquer", + "8_0_TextBox_0": "Slicer commence l'inférence", + "9_0_TextBox_0": "Slicer montre le résultat de la segmentation \nde la prostate basée sur l'IA", + "10_2_TextBox_2": "Cliquez sur Ajouter des données dans le module Bienvenue\nà Slicer\n\n\n\n\n\n\n\n\n\n\nCliquez sur Choisir les fichiers à ajouter et\nnaviguez jusqu'à l'emplacement des\nensembles de données Slicer", + "0_TextBox_2": "30/06/2025", + "3_ArrowText_0": "Cliquez sur Welcome to Slicer dans le menu des modules et naviguez jusqu’à la catégorie Segmentation", + "4_ArrowText_0": "Saisissez le nom du modèle Prostate dans le menu du modèle de Segmentation", + "5_ArrowText_0": "Saisissez le volume T2 d’entrée msdprostate-01-adc", + "6_ArrowText_0": "Et le volume ADC d’entrée msd-prostate-01-adc", + "15_TextBox_0": "Slicer démarre l’inférence", + "9_TextBox_0": "Chargez dataset4_BrainMRI_Glioma", + "10_ArrowText_0": "Sélectionnez le module MONAIAuto3DSeg et entrez \nle nom du modèle, Brain Tumor Segmentation, dans le\n menu Segmentation model", + "13_ArrowText_1": "Une fois la segmentation terminée, ‘Processing finished’ apparaît dans l’interface de Slicer", + "15_ArrowText_0": "Sélectionnez le module MONAIAuto3DSeg et saisissez le nom du modèle Whole Body Segmentation dans le menu du modèle de Segmentation) ;", + "15_ArrowText_1": "Sélectionnez le module MONAIAuto3DSeg et saisissez le nom du modèle Whole Body Segmentation dans le menu du modèle de Segmentation) ;", + "18_TextBox_0": "Slicer affiche le résultat de la segmentation basée sur l’IA \nen utilisant le modèle Whole Body Segmentation TS1-quick", + "31_TextBox_0": "Remerciements", + "13_0_TextBox_0": "Saisissez les volumes d'entrée comme suit :", + "16_2_TextBox_0": "Dans le module Add DICOM Data,\nsélectionnez le patient patient1 et\ncliquez sur charger pour le charger dans Slicer", + "17_0_TextBox_0": "Sélectionnez le module MONAIAuto3DSeg et entrez \nle nom du modèle, Whole Body Segmentation, dans le \n\nmenu Segmentation model", + "17_0_ArrowText_1": "Sélectionnez le modèle Whole Body Segmentation\nTS1 - rapide", + "18_0_TextBox_3": "Sélectionnez le volume d'entrée 6 : CT_Thorax_Abdomen,\n\nCliquez sur Créer une nouvelle segmentation sur Appliquer\nCliquez sur Appliquer pour démarrer la segmentation", + "19_0_TextBox_0": "Slicer commence la segmentation", + "20_0_TextBox_1": "Cliquez sur Afficher en 3D pour voir\n\nla vue 3D des segments" +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_pt-BR.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_pt-BR.json new file mode 100644 index 00000000..b88c3d52 --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_pt-BR.json @@ -0,0 +1,49 @@ +{ + "0_TextBox_0": "AI-based Segmentation in 3D Slicer", + "0_TextBox_1": "Sonia Pujol, Ph. D\nBrigham and Women's Hospital,\nHarvard Medical School\nBoston, MA", + "0_TextBox_3": "Slicer Ribeirão Preto Workshop\nJune 30, 2025", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "1_TextBox_1": "Medical images have traditionally been manually segmented, which is a time-consuming process that requires intensive effort by radiologists and is subject to inter-reader variability.", + "2_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a Model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Workshop", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pretrained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_1": "Multiple modalities Support (CT, MRI).\n\n\nMultiple anatomies (head, thorax, abdomen, pelvis, etc.).\n\n\nMultiple pathologies (tumor, hemorrhage, edema).", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate.\n\n\nSegmentation Task #2: Brain Glioma.\n\n\nSegmentation Task #3: Whole Body Segmentation.", + "8_TextBox_0": "AI Segmentation Task #1: Prostate", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Click on Add Data in the Welcome to Slicer Module\n\nClick on Choose Directory to Add and browse to the location of the Slicer datasets", + "11_TextBox_0": "Slicer loads the prostate MRI data set", + "12_TextBox_0": "Click on Welcome to Slicer in the Modules' menu and browse to the category Segmentation\n\nSelec the MONAI Auto3DSeg module", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "Select the model Prostate - Multisequence", + "14_TextBox_0": "Enter the Input T2 volume msd-prostate-01-adc and the Input ADC volume msd-prostate-01-adc.", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "15_TextBox_0": "Slicer starts the inference", + "16_TextBox_0": "Slicer shows the results of the AI-based prostate segmentation", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer Module\n\nClick on Choose File(s) to Add and browse to the loccation of the Slicer datasets", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t12f\nInput T1C volume: BraTS-GLI_00005-00-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Appply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6: CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the IA-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D SlicerMONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_0": "Acknowledgements", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible by two CZI Essential Open Source Software for Science (EOSS cycle 4 & 5) grants." +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ta.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ta.json new file mode 100644 index 00000000..9390d6bf --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_ta.json @@ -0,0 +1,68 @@ +{ + "1_0_ArrowText_0": "வெல்கம் என்பதில் டேட்டாவைச் சேர் என்பதைக் சொடுக்கு செய்யவும் \nச்லைசர் தொகுதிக்கு", + "2_2_TextBox_1": "சேர்க்க கோப்பகத்தைத் தேர்ந்தெடு என்பதைக் சொடுக்கு செய்யவும் \nமற்றும் இருப்பிடத்தை உலாவவும் \nச்லைசர் தரவுத்தொகுப்புகள்", + "3_0_TextBox_0": "ச்லைசர் புரோச்டேட் எம்ஆர்ஐயை ஏற்றுகிறது \nதரவுத்தொகுப்பு", + "4_3_TextBox_1": "இதில் வெல்கம் டு ச்லைசரை சொடுக்கு செய்யவும் \nதொகுதிகள் பட்டியல் மற்றும் உலாவவும் \n\nவகை பிரிவு. \n\nMONAI Auto3DSeg ஐத் தேர்ந்தெடுக்கவும் \nதொகுதி", + "5_0_ArrowText_0": "மாடல்களின் பெயரை புரோச்டேட் உள்ளிடவும் \nபிரிவு மாதிரி பட்டியல்", + "0_TextBox_0": "AI-based Segmentation in 3D Slicer", + "0_TextBox_1": "Sonia Pujol, Ph. D\nBrigham and Women's Hospital,\nHarvard Medical School\nBoston, MA", + "0_TextBox_3": "Slicer Ribeirão Preto Workshop\nJune 30, 2025", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_0": "Manual vs AI-powered Segmentation", + "1_TextBox_1": "Medical images have traditionally been manually segmented, which is a time-consuming process that requires intensive effort by radiologists and is subject to inter-reader variability.", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a Model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Workshop", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pretrained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_1": "Multiple modalities Support (CT, MRI).\n\n\nMultiple anatomies (head, thorax, abdomen, pelvis, etc.).\n\n\nMultiple pathologies (tumor, hemorrhage, edema).", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate.\n\n\nSegmentation Task #2: Brain Glioma.\n\n\nSegmentation Task #3: Whole Body Segmentation.", + "8_TextBox_0": "AI Segmentation Task #1: Prostate", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "மூளை கட்டி பிரிவின் மாதிரியைத் தேர்ந்தெடுக்கவும் \n(பிராட்ச்) சி.எல்.ஐ", + "11_TextBox_0": "Slicer loads the prostate MRI data set", + "12_TextBox_0": "Click on Welcome to Slicer in the Modules' menu and browse to the category Segmentation\n\nSelec the MONAI Auto3DSeg module", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "ப்ரோச்டேட் - மல்டிசீக்வென்ச் மாதிரியைத் தேர்ந்தெடுக்கவும்", + "14_TextBox_0": "Enter the Input T2 volume msd-prostate-01-adc and the Input ADC volume msd-prostate-01-adc.", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "16_TextBox_0": "Slicer shows the results of the AI-based prostate segmentation", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer Module\n\nClick on Choose File(s) to Add and browse to the loccation of the Slicer datasets", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t12f\nInput T1C volume: BraTS-GLI_00005-00-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Appply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6: CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the IA-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D SlicerMONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible by two CZI Essential Open Source Software for Science (EOSS cycle 4 & 5) grants.", + "7_0_TextBox_0": "உள்ளீடு T2 தொகுதி msd-ஐ உள்ளிடவும் \nprostate-01-adc மற்றும் he Input ADC \nதொகுதி msd-prostate-01-adc", + "7_0_ArrowText_1": "புதிய பிரிவை உருவாக்கு என்பதைத் தேர்ந்தெடுக்கவும் \nவிண்ணப்பிக்கவும்", + "7_0_ArrowText_2": "விண்ணப்பிக்கவும் என்பதைக் சொடுக்கு செய்யவும்", + "8_0_TextBox_0": "ச்லைசர் அனுமானத்தை நட்சத்திரமாக்குகிறது", + "9_0_TextBox_0": "ச்லைசர் AI இன் முடிவைக் காட்டுகிறது. \nஅடிப்படையிலான புரோச்டேட் பிரிவு", + "10_2_TextBox_2": "வெல்கம் என்பதில் டேட்டாவைச் சேர் என்பதைக் சொடுக்கு செய்யவும் \nச்லைசர் தொகுதிக்கு \n\n\n\n\n\n\n\n\n\n\nசேர்ப்பதற்கு கோப்பு(களை) தேர்ந்தெடு என்பதைக் சொடுக்கு செய்யவும் \nச்லைசரின் இடத்திற்கு உலாவவும் \nதரவுத்தொகுப்புகள்", + "15_TextBox_0": "Slicer starts the inference", + "10_ArrowText_0": "MONAIAauto3DSeg தொகுதியைத் தேர்ந்தெடுத்து உள்ளிடவும் \nமாடலின் பெயர் Brain Tumor Segmentation இல் \nபிரிவு மாதிரி பட்டியல்", + "31_TextBox_0": "Acknowledgements", + "13_0_TextBox_0": "உள்ளீட்டு தொகுதிகளை பின்வருமாறு உள்ளிடவும்:", + "16_2_TextBox_0": "சேர் DICOM தரவு தொகுதியில், \nநோயாளி நோயாளி1 மற்றும் \nச்லைசரில் ஏற்றுவதற்கு ஏற்ற என்பதைக் சொடுக்கு செய்யவும்", + "17_0_TextBox_0": "MONAIAauto3DSeg தொகுதியைத் தேர்ந்தெடுத்து உள்ளிடவும் \nமுழு உடல் பிரிவு மாடலின் பெயர் \n\nபிரிவு மாதிரிப் பட்டியல்", + "17_0_ArrowText_1": "முழு உடல் பிரிவின் மாதிரியைத் தேர்ந்தெடுக்கவும் \nTS1 - விரைவானது", + "18_0_TextBox_3": "உள்ளீடு தொகுதி 6 ஐத் தேர்ந்தெடுக்கவும்: CT_Thorax_Abdomen, \n\nApply என்பதில் Create புதிய Segmentation என்பதில் சொடுக்கு செய்யவும் \nபிரிவைத் தொடங்க விண்ணப்பிக்கவும் என்பதைக் சொடுக்கு செய்யவும்", + "19_0_TextBox_0": "ச்லைசர் பிரிவைத் தொடங்குகிறது", + "20_0_TextBox_1": "பார்க்க 3D ஐக் சொடுக்கு செய்க \n\nபிரிவுகள் 3D காட்சி" +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_th.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_th.json new file mode 100644 index 00000000..656bbc2b --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_th.json @@ -0,0 +1,50 @@ +{ + "1_0_ArrowText_0": "คลิกเพิ่มข้อมูลในหน้ายินดีต้อนรับ\nเพื่อไปที่โมดูล Slicer", + "0_TextBox_0": "AI-based Segmentation in 3D Slicer", + "0_TextBox_1": "Sonia Pujol, Ph. D\nBrigham and Women's Hospital,\nHarvard Medical School\nBoston, MA", + "0_TextBox_3": "Slicer Ribeirão Preto Workshop\nJune 30, 2025", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_0": "Manual vs AI-powered Segmentation", + "1_TextBox_1": "Medical images have traditionally been manually segmented, which is a time-consuming process that requires intensive effort by radiologists and is subject to inter-reader variability.", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a Model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Workshop", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pretrained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_1": "Multiple modalities Support (CT, MRI).\n\n\nMultiple anatomies (head, thorax, abdomen, pelvis, etc.).\n\n\nMultiple pathologies (tumor, hemorrhage, edema).", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate.\n\n\nSegmentation Task #2: Brain Glioma.\n\n\nSegmentation Task #3: Whole Body Segmentation.", + "8_TextBox_0": "AI Segmentation Task #1: Prostate", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Click on Add Data in the Welcome to Slicer Module\n\nClick on Choose Directory to Add and browse to the location of the Slicer datasets", + "11_TextBox_0": "Slicer loads the prostate MRI data set", + "12_TextBox_0": "Click on Welcome to Slicer in the Modules' menu and browse to the category Segmentation\n\nSelec the MONAI Auto3DSeg module", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "Select the model Prostate - Multisequence", + "14_TextBox_0": "Enter the Input T2 volume msd-prostate-01-adc and the Input ADC volume msd-prostate-01-adc.", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "16_TextBox_0": "Slicer shows the results of the AI-based prostate segmentation", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer Module\n\nClick on Choose File(s) to Add and browse to the loccation of the Slicer datasets", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t12f\nInput T1C volume: BraTS-GLI_00005-00-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Appply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6: CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the IA-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D SlicerMONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible by two CZI Essential Open Source Software for Science (EOSS cycle 4 & 5) grants.", + "15_TextBox_0": "Slicer starts the inference", + "31_TextBox_0": "Acknowledgements" +} \ No newline at end of file diff --git a/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_uk.json b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_uk.json new file mode 100644 index 00000000..af78e34d --- /dev/null +++ b/Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_uk.json @@ -0,0 +1,78 @@ +{ + "1_0_ArrowText_0": "Натисніть кнопку «Додати дані»\nв модулі «Ласкаво просимо до зрізу»", + "2_2_TextBox_1": "Натисніть «Вибрати каталог для додавання»\nта перейдіть до розташування наборів\nданих Slicer", + "3_0_TextBox_0": "Слайсер завантажує дані МР\n простати", + "4_3_TextBox_1": "Натисніть «Ласкаво просимо до Slicer» у\nменю «Модулі» та перейдіть до\n\nкатегорії «Сегментація».\n\nВиберіть модуль MONAI\nAuto3DSeg", + "5_0_ArrowText_0": "Введіть назву моделі «Простата» в\nменю «Модель сегментації»", + "0_TextBox_0": "AIBasedSegmentationIn3DSlicer", + "0_TextBox_1": "Соня Пуйоль, доктор філ.", + "0_TextBox_3": "AI - Сегментація на основі 3D Slicer", + "1_TextBox_0": "Manual vs AI-powered Segmentation", + "2_TextBox_0": "Slicer завантажує набір даних МРТ простати", + "1_TextBox_1": "Натисніть кнопку «Додати дані» у вікні привітання \tМодуль Slicer", + "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.", + "3_TextBox_0": "AI Terminology", + "3_TextBox_1": "A is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a Model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.", + "4_TextBox_0": "3D Slicer AI Workshop", + "4_TextBox_1": "This tutorial focuses on running inference tasks using various pretrained AI models for automated segmentation of anatomical and pathological structures.", + "5_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "6_TextBox_0": "MONAIAuto3DSeg Slicer extension", + "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.", + "6_TextBox_1": "Натисніть кнопку «Створити нову сегментацію» на сторінці\n«Застосувати»", + "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks", + "7_TextBox_1": "Segmentation Task #1: Prostate.\n\n\nSegmentation Task #2: Brain Glioma.\n\n\nSegmentation Task #3: Whole Body Segmentation.", + "8_TextBox_0": "Slicer показує результат сегментації простати на основі штучного інтелекту", + "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc", + "10_TextBox_1": "Виберіть модель сегментації пухлини головного мозку\n(BRATS) GLI", + "11_TextBox_0": "Введіть вхідні об'єми наступним чином:\nВхідний об'єм T2F: BraTS-GLI_00005-000-t12f\nВхідний об'єм T1C: BraTS-GLI_00005-000-t1c\nВхідний об'єм T1N: BraTS-GLI_00005-000-t1n\nВхідний об'єм T2W: BraTS-GLI_00005-000-t2w\nНатисніть «Створити нову сегментацію» на кнопці «Застосувати»\nНатисніть «Застосувати», щоб розпочати сегментацію", + "12_TextBox_0": "Зрізальник починає виконувати завдання виведення", + "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu", + "13_TextBox_1": "Виберіть модель Простата - Мультисеквенція", + "14_TextBox_0": "У модулі «Додати дані DICOM»\nвиберіть пацієнта patient1 та\nдвічі клацніть на зображенні\nCT_Thorax_Abdomen, щоб завантажити його в\nSlicer", + "14_TextBox_1": "Click on Create new segmentation on Apply", + "16_TextBox_0": "Виберіть вхідний том 6: КТ_Грудної_черевної_плоди,\nНатисніть «Створити нову сегментацію» на кнопці «Застосувати»\nНатисніть «Застосувати», щоб розпочати сегментацію", + "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma", + "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )", + "19_TextBox_1": "Click on Add Data in the Welcome to Slicer Module\n\nClick on Choose File(s) to Add and browse to the loccation of the Slicer datasets", + "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu", + "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI", + "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t12f\nInput T1C volume: BraTS-GLI_00005-00-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Appply\n\nClick on Apply to start the segmentation", + "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI", + "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer", + "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation", + "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen", + "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer", + "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu", + "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick", + "28_TextBox_0": "Select the input Volume 6: CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation", + "29_TextBox_0": "Slicer displays the results of the IA-based segmentation using the Whole Body Segmentation TS1-quick", + "30_TextBox_0": "Conclusion", + "30_TextBox_1": "The 3D SlicerMONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.", + "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible by two CZI Essential Open Source Software for Science (EOSS cycle 4 & 5) grants.", + "7_0_TextBox_0": "Введіть об'єм вхідного T2 msd-\nprostate-01-adc та об'єм вхідного ADC\nmsd-prostate-01-adc", + "7_0_ArrowText_1": "Виберіть «Створити нову сегментацію» на\n«Застосувати»", + "7_0_ArrowText_2": "Натисніть кнопку «Застосувати»", + "8_0_TextBox_0": "Зрізач визначає висновок", + "9_0_TextBox_0": "Зріз показує результат сегментації\nпростати на основі штучного інтелекту", + "10_2_TextBox_2": "Натисніть кнопку «Додати дані» у вікні привітання\nдо модуля Slicer\n\n\n\n\n\n\n\n\n\n\nНатисніть кнопку «Вибрати файл(и) для додавання» та\nперейдіть до розташування зрізу\nнабори даних", + "0_TextBox_2": "30/06/2025", + "3_ArrowText_0": "Натисніть «Ласкаво просимо до Slicer» у\nменю «Модулі» та перейдіть до\nкатегорії «Сегментація».", + "4_ArrowText_0": "Введіть назву моделі «Простата» в\nменю «Модель сегментації»", + "5_ArrowText_0": "Введіть вхідний об'єм T2 msdprostate-01-adc", + "6_ArrowText_0": "І обсяг вхідного АЦП msd-prostate-01-adc", + "15_TextBox_0": "Slicer починає висновок", + "9_TextBox_0": "Завантаження dataset4_BrainMRI_Glioma", + "10_ArrowText_0": "Виберіть модуль MONAIAuto3DSeg і введіть\nназву моделі Brain Tumor Segmentation (Сегментація пухлини мозку) в\nменю Segmentation model (Модель сегментації)", + "13_ArrowText_1": "Після завершення сегментації в графічному інтерфейсі Slicer\nз’явиться напис «Обробку завершено»", + "15_ArrowText_0": "Виберіть модуль MONAIAuto3DSeg та введіть назву моделі\nWhole Body Segmentation (Сегментація всього тіла) у\nменю Модель сегментації);", + "15_ArrowText_1": "Виберіть модуль MONAIAuto3DSeg та введіть назву моделі\nWhole Body Segmentation (Сегментація всього тіла) у\nменю Модель сегментації);", + "18_TextBox_0": "Зріз відображає результат сегментації на основі штучного інтелекту\nза допомогою швидкої сегментації всього тіла TS1", + "31_TextBox_0": "Подяки", + "13_0_TextBox_0": "Введіть вхідні обсяги наступним чином:", + "16_2_TextBox_0": "У модулі «Додати дані DICOM»\nвиберіть пацієнта patient1 і\nнатисніть «Завантажити», щоб завантажити його в Slicer", + "17_0_TextBox_0": "Виберіть модуль MONAIAuto3DSeg і введіть\nназву моделі «Сегментація всього тіла» в\n\nменю «Модель сегментації»", + "17_0_ArrowText_1": "Виберіть модель сегментації всього тіла\nTS1 – швидкий", + "18_0_TextBox_3": "Виберіть вхідний том 6: КТ_Грудної_клітини_Черевини,\n\nНатисніть «Створити нову сегментацію» на «Застосувати».\nНатисніть кнопку «Застосувати», щоб розпочати сегментацію", + "19_0_TextBox_0": "Slicer починає сегментацію", + "20_0_TextBox_1": "Натисніть кнопку «Показати 3D», щоб переглянути\n\n3D-вигляд сегментів" +} \ No newline at end of file diff --git a/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_en.json b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_en.json new file mode 100644 index 00000000..fafa50dc --- /dev/null +++ b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_en.json @@ -0,0 +1,99 @@ +{ + "1_TextBox_1": "This tutorial is an introduction to the basics of loading and viewing DICOM images and 3D models in 3D Slicer.", + "3_TextBox_0": "Tutorial materials", + "4_TextBox_0": "Tutorial dataset", + "33_TextBox_0": "Tutorial dataset", + "5_TextBox_0": "Disclaimer", + "6_TextBox_0": "Tutorial Outline", + "8_LoadingaDICOMvolume_title": "Loading a DICOM volume", + "9_LoadingaDICOMvolume_title": "Loading a DICOM volume", + "8_TextBox_1": "The patient1 study contains a CT Thorax Abdomen dataset", + "11_ArrowText_2": "Select the module \nVolumes", + "10_VisualizingDICOMimages_title": "Visualizing DICOM images", + "11_VisualizingDICOMimages_title": "Visualizing DICOM images", + "12_VisualizingDICOMimages_title": "Visualizing DICOM images", + "13_VisualizingDICOMimages_title": "Visualizing DICOM images", + "14_VisualizingDICOMimages_title": "Visualizing DICOM images", + "15_VisualizingDICOMimages_title": "Visualizing DICOM images", + "16_VisualizingDICOMimages_title": "Visualizing DICOM images", + "17_VisualizingDICOMimages_title": "Visualizing DICOM images", + "18_VisualizingDICOMimages_title": "Visualizing DICOM images", + "16_TextBox_0": "Slicer switches the layout \nto Conventional \nWidescreen layout", + "17_TextBox_0": "Use the right mouse button in the \n3D Viewer to zoom in and out", + "19_3DViewerController_title": "3D Viewer Controller", + "20_3DViewerController_title": "3D Viewer Controller", + "22_TextBox_0": "Volume Rendering", + "23_VolumeRendering_title": "Volume Rendering", + "24_VolumeRendering_title": "Volume Rendering", + "25_VolumeRendering_title": "Volume Rendering", + "26_VolumeRendering_title": "Volume Rendering", + "27_VolumeRendering_title": "Volume Rendering", + "28_VolumeRendering_title": "Volume Rendering", + "29_VolumeRendering_title": "Volume Rendering", + "30_VolumeRendering_title": "Volume Rendering", + "31_VolumeRendering_title": "Volume Rendering", + "24_TextBox_2": "Select VTK GPU Ray Casting Rendering\nClick on the eye icon in the Volume tab to display \nthe volume rendered image in the 3D viewer", + "26_ArrowText_0": "Click on Display ROI to \ndisplay a region of interest \n(ROI) in the 3D viewer and \ncheck the option Enable", + "28_ArrowText_0": "Click on the eye icon to \ndisplay the volume rendered \nimage", + "29_TextBox_0": "Slicer displays the \nvolume rendered \nimage of the left kidney ", + "30_TextBox_0": "Extend the ROI to generate \na volume rendered image of \nthe right kidney", + "34_TextBox_0": "Slicer Scene", + "35_LoadingaScene_title": "Loading a Scene", + "35_TextBox_0": "Slicer displays a 3D \nsurface model of the \nhead and 2D MRI slices", + "36_Viewing3Dmodels_title": "Viewing 3D models", + "37_Viewing3Dmodels_title": "Viewing 3D models", + "38_Viewing3Dmodels_title": "Viewing 3D models", + "39_Viewing3Dmodels_title": "Viewing 3D models", + "40_Viewing3Dmodels_title": "Viewing 3D models", + "36_ArrowText_0": "Position the cursor over \nthe pin icon to reveal the \nslice menu and click on \nthe eye icon to display the \naxial slice in the 3D viewer", + "41_Interactingwith3Dmodels_title": "Interacting with 3D models", + "42_Interactingwith3Dmodels_title": "Interacting with 3D models", + "43_Interactingwith3Dmodels_title": "Interacting with 3D models", + "44_Interactingwith3Dmodels_title": "Interacting with 3D models", + "38_ArrowText_0": "Lower the opacity of \nthe Skin model using \nthe visibility slider", + "38_TextBox_1": "The skull bone and \neyeballs models appear \nthrough the skin", + "40_TextBox_2": "The white matter and \noptic nerve models \nappear through the skin", + "40_ArrowText_1": "Select the skull bone \nmodel and click on the \neye icon to turn off its \nvisibility", + "0_TextBox_0": "Basics of Data Loading and 3D Visualization in 3D Slicer", + "0_TextBox_1": "Author: Sonia Pujol, Ph.D.", + "0_TextBox_2": "24/11/2024", + "0_TextBox_3": "Assistant Professor of Radiology Brigham and Women’s Hospital Harvard Medical School", + "1_TextBox_0": "Overall Goal", + "2_TextBox_0": "Learning Objectives", + "2_TextBox_1": " • Following this tutorial, you will be able\n\n• to load and visualize DICOM images in Slicer\n\n• to perform volume rendering of CT data\n\n• to load and visualize 3D models reconstructed from MRI data", + "3_TextBox_1": "• 3D Slicer version 5.10\n\n• 3D VisualizationDataSet.zip", + "4_TextBox_1": "The file 3DVisualizationDataset.zip contains two directories:\n\n- dataset1_Thorax_Abdomen \n- dataset2_Head\n\nUnzip the file 3DVisualizationDataset.zip on your computer to access the datasets", + "5_TextBox_1": "• 3D Slicer is a free open source software application distributed under a BSD style license. \n\n\n• The software is not FDA approved or CE-Marked, and is for research use only.\nTutorial Outline", + "6_TextBox_1": "• Part 1: Loading and Viewing DICOM data\n\n• Part 2: Volume Rendering\n\n\n• Part 3: Loading and Viewing 3D models", + "7_TextBox_0": "Part 1: DICOM Data Loading", + "8_TextBox_0": "Slicer displays the user interface of the DICOM module", + "9_ArrowText_1": "Select patient1 and click on Load \nto load the dataset in Slicer", + "10_TextBox_0": "Slicer displays the axial, coronal \nand sagittal images of the CT \nThorax Abdomen dataset ", + "11_ArrowText_1": "Left click on DICOM to display \nthe list of modules of Slicer", + "12_ArrowText_0": "Click on the CT-abdomen \npreset to automatically adjust \nthe window/level display of the \nCT dataset", + "13_TextBox_1": "Position the mouse cursor \nover the red banner in the \nRed Viewer to display the slice \nmenu.\n\n\nClick on the Links icon to link \nthe slice controls across all \nSlice Viewers. \n\n\nClick on the Eye icon to\ndisplay the three anatomical \nslices in the 3D Viewer", + "14_TextBox_0": "The three anatomical slices \nappear in the 3D viewer.", + "15_ArrowText_0": "Click on the Slicer layout menu \nicon, and select the \nConventional Widescreen layout", + "18_TextBox_0": "Use the left mouse button in the \n3D Viewer to rotate the images", + "19_TextBox_1": "Position the mouse cursor over \nthe pin icon in the blue banner \nof the 3D viewer window to \ndisplay the 3DView controller\n\nClick on the second icon on the \ntop row of the 3DView \ncontroller to center the 3D view \non the scene", + "20_ArrowText_1": "Select the Volume Rendering \nmodule in the list of modules ", + "21_TextBox_0": "Part 2: Volume Rendering", + "22_TextBox_1": "• Volume rendering \ntechniques enable 3D \nvisualization of 3D \ndatasets\n\n• The Volume Rendering \nmodule in Slicer enables \ninteractive 3D visualization \nof DICOM images", + "23_ArrowText_0": "Click on Preset in the Display tab \nand select the preset CT-Cardiac3 ", + "25_ArrowText_0": "Use the shift slider to \nchange the transfer \nfunction and display the\naorta", + "27_TextBox_0": "Turn off the visibility of the \naxial, sagittal and coronal \nslices in the 2D viewer \n\n\nPosition the ROI around the \nleft kidney using the color \nhandles", + "31_ArrowText_1": "Click on File, then Close Scene\nin the main menu", + "32_TextBox_0": "Part 3: Loading and \nviewing 3D models\n", + "33_TextBox_1": "• The directory dataset2_Head contains the Slicer scene called Head_scene.mrb\n\n• The scene contains 3D models from the SPL brain atlas developed by the department of Radiology at Brigham and Women’s Hospital, Harvard Medical School (NIH P41 RR013218, NIH R01 MH05074)", + "34_TextBox_1": "Slicer stores all loaded data in a repository called a scene\n\n\nEach data set, such as an image volume, surface model, or point set, is represented as a node in a Slicer scene.\n\n\nAll Slicer modules operate on the data stored in a Slicer scene.", + "37_ArrowText_1": "Select the Models module \nin the list of models", + "39_ArrowText_0": "Slicer displays the list of \n3D models loaded in the \nscene\n\nSelect the model Skin.vtk", + "41_ArrowText_0": "Click on the eye icon to \ndisplay the coronal slice \nin the 3D viewer", + "42_ArrowText_2": "Select the hemispheric \nwhite matter model and \nselect the option Clipping", + "43_TextBox_0": "Move the coronal slice \nposteriorily to display the \noptic chiasm", + "44_TextBox_0": "Slicer displays a 3D view of \nthe optic chiasm", + "45_TextBox_1": "• 3D Slicer provides advanced functionalities for loading and viewing 3D medical imaging data\n\n• The tutorial demonstrates how to use volume \nrendering and 3D surface modeling for \ninteractive visualization of CT and MRI data\n\n\nContact: spujol@bwh.harvard.edu", + "46_TextBox_0": "Acknowledgements", + "46_TextBox_1": "Neuroimage Analysis Center (NIBIB P41 EB015902)", + "45_TextBox_0": "Conclusion" +} \ No newline at end of file diff --git a/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_es.json b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_es.json new file mode 100644 index 00000000..8019fbb8 --- /dev/null +++ b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_es.json @@ -0,0 +1,121 @@ +{ + "0_TextBox_0": "Basics of Data Loading and 3D Visualization in 3D Slicer", + "0_TextBox_1": "Author: Sonia Pujol, Ph.D.", + "0_TextBox_2": "24/11/2024", + "0_TextBox_3": "Assistant Professor of Radiology Brigham and Women’s Hospital Harvard Medical School", + "1_TextBox_0": "Overall Goal", + "2_TextBox_0": "Learning Objectives", + "1_TextBox_1": "Este tutorial es una introducción a los conceptos básicos de carga y visualización de imágenes DICOM y modelos 3D en 3D Slicer.", + "2_TextBox_1": " • Following this tutorial, you will be able\n\n• to load and visualize DICOM images in Slicer\n\n• to perform volume rendering of CT data\n\n• to load and visualize 3D models reconstructed from MRI data", + "3_TextBox_0": "Materiales tutoriales", + "3_TextBox_1": "• 3D Slicer version 5.10\n\n• 3D VisualizationDataSet.zip", + "4_TextBox_0": "Conjunto de datos del tutorial", + "33_TextBox_0": "Pulse en el Archivo ", + "4_TextBox_1": "The file 3DVisualizationDataset.zip contains two directories:\n\n- dataset1_Thorax_Abdomen \n- dataset2_Head\n\nUnzip the file 3DVisualizationDataset.zip on your computer to access the datasets", + "5_TextBox_0": "Descargo de responsabilidad", + "5_TextBox_1": "• 3D Slicer is a free open source software application distributed under a BSD style license. \n\n\n• The software is not FDA approved or CE-Marked, and is for research use only.\nTutorial Outline", + "6_TextBox_0": "Esquema del tutorial", + "6_TextBox_1": "• Part 1: Loading and Viewing DICOM data\n\n• Part 2: Volume Rendering\n\n\n• Part 3: Loading and Viewing 3D models", + "7_TextBox_0": "Part 1: DICOM Data Loading", + "8_LoadingaDICOMvolume_title": "Cargar un volumen DICOM", + "9_LoadingaDICOMvolume_title": "Cargar un volumen DICOM", + "8_ArrowText_0": "Arrastre y suelte el directorio\ndataset1_Thorax_Abdomen\nen Slicer", + "9_TextBox_0": "Haga clic en Aceptar para\ncargar el directorio en la\nbase de datos DICOM", + "10_TextBox_0": "Slicer displays the axial, coronal \nand sagittal images of the CT \nThorax Abdomen dataset ", + "8_TextBox_1": "El estudio patient1 contiene un conjunto de datos de TC de Tórax y Abdomen", + "11_ArrowText_1": "Left click on DICOM to display \nthe list of modules of Slicer", + "12_TextBox_0": "Slicer muestra las imágenes axiales,\ncoronales y sagitales del conjunto de\ndatos de TC de tórax y abdomen \n", + "11_ArrowText_2": "Seleccione el módulo\nVolúmenes", + "13_TextBox_2": "Pulse al izquierdo en DICOM para\nmostrar la lista de módulos de Slicer. ", + "14_ArrowText_0": "Pulse en el CT-abdomen\npreseleccione a ajuste automático\nla ventana/nivel exhibido del\nconjunto de datos CT ", + "15_ArrowText_0": "Click on the Slicer layout menu \nicon, and select the \nConventional Widescreen layout", + "15_ArrowText_1": "Pulsa en el icono de Enlaces \npara vincular los controles de \ncorte en todos los Visores de Cortes. ", + "15_ArrowText_2": "Pulse en el icono del ojo para\nvisualizar los tres cortes anatómicos\nen el visor 3D", + "16_TextBox_0": "Slicer cambia el distribución a\nPantalla Ancha Convencional", + "10_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "11_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "12_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "13_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "14_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "15_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "16_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "17_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "18_VisualizingDICOMimages_title": "Visualizar imágenes DICOM", + "17_ArrowText_1": "Pulse en el icono del menú de diseño\nde la segmentación de datos y seleccione\nel diseño de pantalla ancha convencional ", + "19_VisualizingDICOMimage_title": "Visualizando imagen DICOM", + "20_VisualizingDICOMimage_title": "Visualizando imagen DICOM", + "17_TextBox_0": "Utilice el botón rojo del ratón en\nel Visor 3D para ampliar y reducir", + "20_TextBox_0": "Utilice al botón izquierdo del ratón\nen el Visor 3D para rotar las imágenes ", + "19_3DViewerController_title": "Controlador del Visor 3D", + "20_3DViewerController_title": "Controlador del Visor 3D", + "21_TextBox_0": "Part 2: Volume Rendering", + "22_TextBox_0": "Representación de Volumen", + "23_TextBox_0": "Parte 2\nRepresentar Volumen", + "23_VolumeRendering_title": "Representación de Volumen", + "24_VolumeRendering_title": "Representación de Volumen", + "25_VolumeRendering_title": "Representación de Volumen", + "26_VolumeRendering_title": "Representación de Volumen", + "27_VolumeRendering_title": "Representación de Volumen", + "28_VolumeRendering_title": "Representación de Volumen", + "29_VolumeRendering_title": "Representación de Volumen", + "30_VolumeRendering_title": "Representación de Volumen", + "31_VolumeRendering_title": "Representación de Volumen", + "24_TextBox_1": "-Técnicas de representar\nel volumen habilita \nvisualización en 3D del\nconjunto de datos\n-El módulo de \nRepresentación de Volumen\nen Slice habilita la visualización\ninteractiva de visualización en 3D\nde imágenes DICOM ", + "25_TextBox_0": "Pulse en Preajuste en la pestaña Pantalla y\nseleccione el preajuste CT-Cardiac3", + "24_TextBox_2": "Seleccione Representación de Ray Casting por GPU VTK.\nPulse en el icono del ojo en la pestaña Volumen para exhibir\nla imagen representada del volumen en el visor 3D", + "27_ArrowText_0": "Utilice el control deslizante de\ndesplazamiento para cambiar la\nfunción de transferencia y exhibir\nla aorta", + "26_ArrowText_0": "Pulse en Mostrar ROI para\nmostrar una región de interés\n(ROI) en el visor 3D y marque\nla opción Habilitar", + "29_ArrowText_0": "Apaga la visibilidad de los\ncortes axial, sagital y coronal\nen el visor 2D. Coloque la ROI\nalrededor del riñón izquierdo\nusando los controles de color", + "28_ArrowText_0": "Pulse en el icono del ojo\npara mostrar la imagen del\nvolumen representado", + "29_TextBox_0": "Slicer exhibe la imagen\nrepresentada por volumen\ndel riñón izquierdo ", + "30_TextBox_0": "Ampliar la ROI para generar\nuna imagen representada en\nvolumen del riñón derecho", + "34_TextBox_0": "Escena Slicer", + "35_TextBox_1": "*Slicer almacena todos los datos cargados en un repositorio llamado escena\n\n*Cada conjunto de datos, como un volumen de imagen, un modelo de superficie o un conjunto de puntos, se representa como un nodo en una escena de Slicer.\n\n*Todos los módulos de Slicer operan con los datos almacenados en una escena de Slicer", + "36_TextBox_1": "*El directorio dataset2_Head contiene\nla escena de Slicer llamada\nHead_scene.mrb\n\n*Esta escena contiene modelos 3D\ndel atlas cerebral SPL desarrollado\npor el Departamento de Radiología\ndel Hospital Brigham and Women’s\nde la Facultad de Medicina de Harvard\n(NIH P41 RR013218, NIH R01 MH05074)", + "35_LoadingaScene_title": "Cargando una Escena", + "37_ArrowText_0": "Arrastre y suelte el archivo\nHead_Scene.mrb, ubicado en\nel directorio dataset2_Head,\nen Slicer", + "35_TextBox_0": "Slicer exhibe un modelo de\nsuperficie 3D de la cabeza y cortes\nde resonancia magnética 2D", + "36_Viewing3Dmodels_title": "Viendo modelos 3D", + "37_Viewing3Dmodels_title": "Viendo modelos 3D", + "38_Viewing3Dmodels_title": "Viendo modelos 3D", + "39_Viewing3Dmodels_title": "Viendo modelos 3D", + "40_Viewing3Dmodels_title": "Viendo modelos 3D", + "36_ArrowText_0": "Coloque el cursor sobre el\nicono del alfiler para abrir el\nmenú de cortes y pulse sobre\nel icono del ojo para ver el\ncorte axial en el visor 3D", + "40_ArrowText_0": "Selecciona los Modelos del \nmódulo en el listado de modelos ", + "41_ArrowText_0": "Pulse en el icono del ojo\npara visualizar el corte\ncoronal en el visor 3D", + "41_Interactingwith3Dmodels_title": "Interactuar con modelos 3D", + "42_Interactingwith3Dmodels_title": "Interactuar con modelos 3D", + "43_Interactingwith3Dmodels_title": "Interactuar con modelos 3D", + "44_Interactingwith3Dmodels_title": "Interactuar con modelos 3D", + "38_ArrowText_0": "Disminuya la opacidad\ndel modelo de piel con\nel control deslizante de\nvisibilidad", + "38_TextBox_1": "Los modelos de huesos\ndel cráneo y globos oculares\naparecen a través de la piel", + "40_TextBox_2": "Los modelos de sustancia\nblanca y nervio óptico\naparecen a través de la piel", + "40_ArrowText_1": "Seleccione el modelo del\nhueso del cráneo y pulse\nen el icono del ojo para\ndesactivar su visibilidad", + "8_TextBox_0": "Slicer displays the user interface of the DICOM module", + "9_ArrowText_1": "Select patient1 and click on Load \nto load the dataset in Slicer", + "12_ArrowText_0": "Click on the CT-abdomen \npreset to automatically adjust \nthe window/level display of the \nCT dataset", + "13_TextBox_1": "Position the mouse cursor \nover the red banner in the \nRed Viewer to display the slice \nmenu.\n\n\nClick on the Links icon to link \nthe slice controls across all \nSlice Viewers. \n\n\nClick on the Eye icon to\ndisplay the three anatomical \nslices in the 3D Viewer", + "14_TextBox_0": "The three anatomical slices \nappear in the 3D viewer.", + "18_TextBox_0": "Use the left mouse button in the \n3D Viewer to rotate the images", + "19_TextBox_1": "Position the mouse cursor over \nthe pin icon in the blue banner \nof the 3D viewer window to \ndisplay the 3DView controller\n\nClick on the second icon on the \ntop row of the 3DView \ncontroller to center the 3D view \non the scene", + "20_ArrowText_1": "Select the Volume Rendering \nmodule in the list of modules ", + "22_TextBox_1": "• Volume rendering \ntechniques enable 3D \nvisualization of 3D \ndatasets\n\n• The Volume Rendering \nmodule in Slicer enables \ninteractive 3D visualization \nof DICOM images", + "23_ArrowText_0": "Click on Preset in the Display tab \nand select the preset CT-Cardiac3 ", + "25_ArrowText_0": "Use the shift slider to \nchange the transfer \nfunction and display the\naorta", + "27_TextBox_0": "Turn off the visibility of the \naxial, sagittal and coronal \nslices in the 2D viewer \n\n\nPosition the ROI around the \nleft kidney using the color \nhandles", + "31_ArrowText_1": "Click on File, then Close Scene\nin the main menu", + "32_TextBox_0": "Part 3: Loading and \nviewing 3D models\n", + "33_TextBox_1": "• The directory dataset2_Head contains the Slicer scene called Head_scene.mrb\n\n• The scene contains 3D models from the SPL brain atlas developed by the department of Radiology at Brigham and Women’s Hospital, Harvard Medical School (NIH P41 RR013218, NIH R01 MH05074)", + "34_TextBox_1": "Slicer stores all loaded data in a repository called a scene\n\n\nEach data set, such as an image volume, surface model, or point set, is represented as a node in a Slicer scene.\n\n\nAll Slicer modules operate on the data stored in a Slicer scene.", + "37_ArrowText_1": "Select the Models module \nin the list of models", + "39_ArrowText_0": "Slicer displays the list of \n3D models loaded in the \nscene\n\nSelect the model Skin.vtk", + "42_ArrowText_2": "Seleccione el modelo de\nmateria blanca hemisférico y\nseleccione la opción Recorte", + "43_TextBox_0": "Mueva el corte coronal\nposteriormente para visualizar\nel quiasma óptico", + "44_TextBox_0": "Slicer exhibe una vista 3D\ndel quiasma óptico", + "45_TextBox_1": "• 3D Slicer provides advanced functionalities for loading and viewing 3D medical imaging data\n\n• The tutorial demonstrates how to use volume \nrendering and 3D surface modeling for \ninteractive visualization of CT and MRI data\n\n\nContact: spujol@bwh.harvard.edu", + "46_TextBox_0": "Agradecimientos", + "46_TextBox_1": "Neuroimage Analysis Center (NIBIB P41 EB015902)", + "48_TextBox_1": "Dentro de Análisis\nNeuroimage \n(NIBIB P41 EB015902)", + "45_TextBox_0": "Conclusión", + "49_TextBox_1": "*3D Slicer ofrece funciones avanzadas para cargar y\nvisualizar datos de imágenes médicas en 3D.\n\n*El tutorial muestra cómo usar la representación\nvolumétrica y el modelado de superficies en 3D\npara la visualización interactiva de datos de TC y RM.\n\nContacto: spujol@bwh.harvard.edu" +} \ No newline at end of file diff --git a/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_fr.json b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_fr.json new file mode 100644 index 00000000..9a85b5a6 --- /dev/null +++ b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_fr.json @@ -0,0 +1,117 @@ +{ + "0_TextBox_0": "Basics of Data Loading and 3D Visualization in 3D Slicer", + "0_TextBox_1": "Author: Sonia Pujol, Ph.D.", + "0_TextBox_2": "24/11/2024", + "0_TextBox_3": "Assistant Professor of Radiology Brigham and Women’s Hospital Harvard Medical School", + "1_TextBox_0": "Overall Goal", + "2_TextBox_0": "Learning Objectives", + "1_TextBox_1": "Ce tutoriel est une introduction aux notions de base du chargement et de l’affichage des images DICOM et des modèles 3D dans 3D Slicer.", + "2_TextBox_1": " • Following this tutorial, you will be able\n\n• to load and visualize DICOM images in Slicer\n\n• to perform volume rendering of CT data\n\n• to load and visualize 3D models reconstructed from MRI data", + "3_TextBox_0": "Matériels du tutoriel", + "3_TextBox_1": "• 3D Slicer version 5.10\n\n• 3D VisualizationDataSet.zip", + "4_TextBox_0": "Jeu de données du tutoriel", + "33_TextBox_0": "Cliquez sur File ", + "4_TextBox_1": "The file 3DVisualizationDataset.zip contains two directories:\n\n- dataset1_Thorax_Abdomen \n- dataset2_Head\n\nUnzip the file 3DVisualizationDataset.zip on your computer to access the datasets", + "5_TextBox_0": "Avertissement", + "5_TextBox_1": "• 3D Slicer is a free open source software application distributed under a BSD style license. \n\n\n• The software is not FDA approved or CE-Marked, and is for research use only.\nTutorial Outline", + "6_TextBox_0": "Plan du tutoriel", + "6_TextBox_1": "• Part 1: Loading and Viewing DICOM data\n\n• Part 2: Volume Rendering\n\n\n• Part 3: Loading and Viewing 3D models", + "7_TextBox_0": "Part 1: DICOM Data Loading", + "8_LoadingaDICOMvolume_title": "Chargement d’un volume DICOM", + "9_LoadingaDICOMvolume_title": "Chargement d’un volume DICOM", + "8_ArrowText_0": "Glissez-déposez le répertoire \ndataset1_Thorax_Abdomen \ndans Slicer", + "9_TextBox_0": "Cliquez sur OK pour charger \nle répertoire dans \nla base de données DICOM", + "8_TextBox_0": "Slicer displays the user interface of the DICOM module", + "8_TextBox_1": "L’étude patient1 contient un jeu de données CT Thorax Abdomen", + "11_ArrowText_1": "Left click on DICOM to display \nthe list of modules of Slicer", + "12_TextBox_0": "Slicer affiche les images axiale, coronale \net sagittale du jeu de données \nCT Thorax Abdomen. \n", + "11_ArrowText_2": "Sélectionnez le module Volumes", + "13_TextBox_2": "Clic gauche sur DICOM pour afficher la liste des modules de Slicer. ", + "12_ArrowText_0": "Click on the CT-abdomen \npreset to automatically adjust \nthe window/level display of the \nCT dataset", + "15_ArrowText_0": "Click on the Slicer layout menu \nicon, and select the \nConventional Widescreen layout", + "15_ArrowText_1": "Cliquez sur l’icône Links pour relier les contrôles des coupes entre toutes les Visionneuses de Coupes. ", + "15_ArrowText_2": "Cliquez sur l’icône Eye pour afficher les trois coupes anatomiques dans la Visionneuse 3D", + "14_TextBox_0": "The three anatomical slices \nappear in the 3D viewer.", + "10_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "11_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "12_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "13_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "14_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "15_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "16_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "17_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "18_VisualizingDICOMimages_title": "Visualisation d'images DICOM", + "17_ArrowText_1": "Cliquez sur l’icône du menu de mise en page de Slicer et sélectionnez la mise en page Conventional Widescreen. ", + "16_TextBox_0": "Slicer passe à la mise en page Conventional Widescreen", + "19_VisualizingDICOMimage_title": "Visualisation d’une image DICOM", + "20_VisualizingDICOMimage_title": "Visualisation d’une image DICOM", + "17_TextBox_0": "Utilisez le bouton droit de la souris dans la Visionneuse 3D pour zoomer avant et arrière", + "18_TextBox_0": "Use the left mouse button in the \n3D Viewer to rotate the images", + "19_3DViewerController_title": "Contrôleur de la Visionneuse 3D", + "20_3DViewerController_title": "Contrôleur de la Visionneuse 3D", + "19_TextBox_0": "Placez le curseur de la souris sur l’icône en forme d’épingle dans la bande bleue de la fenêtre de la visionneuse 3D pour afficher le contrôleur 3DView.\nCliquez sur la deuxième icône de la première rangée du contrôleur 3DView pour centrer la vue 3D sur la scène.", + "22_TextBox_0": "Rendu Volumique", + "23_TextBox_0": "Partie 2 Rendu Volumique", + "23_VolumeRendering_title": "Rendu Volumique", + "24_VolumeRendering_title": "Rendu Volumique", + "25_VolumeRendering_title": "Rendu Volumique", + "26_VolumeRendering_title": "Rendu Volumique", + "27_VolumeRendering_title": "Rendu Volumique", + "28_VolumeRendering_title": "Rendu Volumique", + "29_VolumeRendering_title": "Rendu Volumique", + "30_VolumeRendering_title": "Rendu Volumique", + "31_VolumeRendering_title": "Rendu Volumique", + "24_TextBox_1": "- Les techniques de rendu volumique permettent la visualisation 3D des jeux de données 3D\n- Le module Volume Rendering de Slicer permet la visualisation 3D interactive des images DICOM. ", + "25_TextBox_0": "Cliquez sur Preset dans l’onglet Display et sélectionnez le préréglage CT-Cardiac3", + "24_TextBox_2": "Sélectionnez VTK GPU Ray Casting Rendering\nCliquez sur l’icône Eye dans l’onglet Volume pour afficher l’image en rendu volumique dans la visionneuse 3D", + "25_ArrowText_0": "Use the shift slider to \nchange the transfer \nfunction and display the\naorta", + "26_ArrowText_0": "Cliquez sur Display ROI pour afficher une région d’intérêt (ROI) dans la visionneuse 3D et cochez l’option Enable", + "27_ArrowText_0": "Désactivez la visibilité des coupes axiale, sagittale et coronale dans la visionneuse 2D.\nPositionnez la ROI autour du rein gauche en utilisant les poignées colorées.", + "28_ArrowText_0": "Cliquez sur l’icône Eye pour afficher l’image en rendu volumique", + "29_TextBox_0": "Slicer affiche l’image en rendu volumique du rein gauche. ", + "30_TextBox_0": "Étendez la ROI pour générer une image en rendu volumique du rein droit", + "34_TextBox_0": "Scène Slicer", + "35_TextBox_1": "*Slicer stocke toutes les données chargées dans un dépôt appelé scène\n\n*Chaque jeu de données, comme un volume d’image, un modèle de surface ou un ensemble de points, est représenté par un nœud dans une scène Slicer\n\n*Tous les modules de Slicer opèrent sur les données stockées dans une scène Slicer", + "36_TextBox_1": "*Le répertoire dataset2_Head contient la scène Slicer appelée Head_scene.mrb\n\n*La scène contient des modèles 3D de l’atlas cérébral SPL développé par le département de radiologie du Brigham and Women’s Hospital, Harvard Medical School (NIH P41 RR013218, NIH R01 MH05074)", + "35_LoadingaScene_title": "Chargement d’une scène", + "37_ArrowText_0": "Sélectionnez le module Models dans la liste des modules. ", + "35_TextBox_0": "Slicer affiche un modèle de surface 3D de la tête ainsi que des coupes IRM 2D", + "36_Viewing3Dmodels_title": "Visualisation des modèles 3D", + "37_Viewing3Dmodels_title": "Visualisation des modèles 3D", + "38_Viewing3Dmodels_title": "Visualisation des modèles 3D", + "39_Viewing3Dmodels_title": "Visualisation des modèles 3D", + "40_Viewing3Dmodels_title": "Visualisation des modèles 3D", + "36_ArrowText_0": "Placez le curseur sur l’icône en forme d’épingle pour afficher le menu des coupes, puis cliquez sur l’icône en forme d’œil pour afficher la coupe axiale dans la visionneuse 3D", + "38_ArrowText_0": "Réduisez l’opacité du modèle Skin en utilisant le curseur de visibilité", + "41_Interactingwith3Dmodels_title": "Interaction avec les modèles 3D", + "42_Interactingwith3Dmodels_title": "Interaction avec les modèles 3D", + "43_Interactingwith3Dmodels_title": "Interaction avec les modèles 3D", + "44_Interactingwith3Dmodels_title": "Interaction avec les modèles 3D", + "13_TextBox_1": "Position the mouse cursor \nover the red banner in the \nRed Viewer to display the slice \nmenu.\n\n\nClick on the Links icon to link \nthe slice controls across all \nSlice Viewers. \n\n\nClick on the Eye icon to\ndisplay the three anatomical \nslices in the 3D Viewer", + "19_TextBox_1": "Position the mouse cursor over \nthe pin icon in the blue banner \nof the 3D viewer window to \ndisplay the 3DView controller\n\nClick on the second icon on the \ntop row of the 3DView \ncontroller to center the 3D view \non the scene", + "21_TextBox_0": "Part 2: Volume Rendering", + "22_TextBox_1": "• Volume rendering \ntechniques enable 3D \nvisualization of 3D \ndatasets\n\n• The Volume Rendering \nmodule in Slicer enables \ninteractive 3D visualization \nof DICOM images", + "27_TextBox_0": "Turn off the visibility of the \naxial, sagittal and coronal \nslices in the 2D viewer \n\n\nPosition the ROI around the \nleft kidney using the color \nhandles", + "31_ArrowText_1": "Click on File, then Close Scene\nin the main menu", + "32_TextBox_0": "Part 3: Loading and \nviewing 3D models\n", + "33_TextBox_1": "• The directory dataset2_Head contains the Slicer scene called Head_scene.mrb\n\n• The scene contains 3D models from the SPL brain atlas developed by the department of Radiology at Brigham and Women’s Hospital, Harvard Medical School (NIH P41 RR013218, NIH R01 MH05074)", + "34_TextBox_1": "Slicer stores all loaded data in a repository called a scene\n\n\nEach data set, such as an image volume, surface model, or point set, is represented as a node in a Slicer scene.\n\n\nAll Slicer modules operate on the data stored in a Slicer scene.", + "37_ArrowText_1": "Select the Models module \nin the list of models", + "38_TextBox_1": "Les modèles du crâne et des yeux apparaissent à travers la peau", + "39_ArrowText_0": "Slicer displays the list of \n3D models loaded in the \nscene\n\nSelect the model Skin.vtk", + "40_TextBox_2": "Les modèles de la matière blanche et du nerf optique apparaissent à travers la peau", + "45_TextBox_1": "• 3D Slicer provides advanced functionalities for loading and viewing 3D medical imaging data\n\n• The tutorial demonstrates how to use volume \nrendering and 3D surface modeling for \ninteractive visualization of CT and MRI data\n\n\nContact: spujol@bwh.harvard.edu", + "46_TextBox_1": "Neuroimage Analysis \nCenter \n(NIBIB P41 EB015902)", + "40_ArrowText_1": "Sélectionnez le modèle skull bone et cliquez sur l’icône Eye pour désactiver sa visibilité", + "9_ArrowText_1": "Select patient1 and click on Load \nto load the dataset in Slicer", + "10_TextBox_0": "Slicer displays the axial, coronal \nand sagittal images of the CT \nThorax Abdomen dataset ", + "20_ArrowText_1": "Select the Volume Rendering \nmodule in the list of modules ", + "23_ArrowText_0": "Click on Preset in the Display tab \nand select the preset CT-Cardiac3 ", + "41_ArrowText_0": "Cliquez sur l’icône Eye pour afficher la coupe coronale dans la visionneuse 3D", + "42_ArrowText_2": "Sélectionnez le modèle hemispheric white matter et activez l’option Clipping", + "43_TextBox_0": "Déplacez la coupe coronale vers l’arrière pour afficher le chiasma optique", + "44_TextBox_0": "Slicer affiche une vue 3D du chiasma optique", + "46_TextBox_0": "Remerciements", + "45_TextBox_0": "Conclusion", + "49_TextBox_1": "*3D Slicer offre des fonctionnalités avancées pour le chargement et la visualisation des données d’imagerie médicale 3D\n\n*Le tutoriel montre comment utiliser le rendu volumique et la modélisation de surfaces 3D pour la visualisation interactive des données CT et IRM\n\nContact : spujol@bwh.harvard.edu" +} \ No newline at end of file diff --git a/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_pt-BR.json b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_pt-BR.json new file mode 100644 index 00000000..ef5e24fe --- /dev/null +++ b/Tutorials/STC-VIS-101_VisualizationTutorial/Translations/text_dict_pt-BR.json @@ -0,0 +1,99 @@ +{ + "0_TextBox_0": "Noções básicas de carregamento de dados e visualização 3D no 3D Slicer", + "0_TextBox_1": "Author: Sonia Pujol, Ph.D.", + "0_TextBox_2": "24/11/2024", + "0_TextBox_3": "Assistant Professor of Radiology Brigham and Women’s Hospital Harvard Medical School", + "1_TextBox_0": "Objetivo geral", + "1_TextBox_1": "Este tutorial é uma introdução aos conceitos básicos de carregamento e visualização de imagens DICOM e modelos 3D no 3D Slicer.", + "2_TextBox_0": "Objectivos de aprendizagem", + "2_TextBox_1": " • Following this tutorial, you will be able\n\n• to load and visualize DICOM images in Slicer\n\n• to perform volume rendering of CT data\n\n• to load and visualize 3D models reconstructed from MRI data", + "3_TextBox_0": "Materiais do tutorial", + "3_TextBox_1": "• 3D Slicer version 5.10\n\n• 3D VisualizationDataSet.zip", + "4_TextBox_0": "Tutorial dataset", + "4_TextBox_1": "The file 3DVisualizationDataset.zip contains two directories:\n\n- dataset1_Thorax_Abdomen \n- dataset2_Head\n\nUnzip the file 3DVisualizationDataset.zip on your computer to access the datasets", + "5_TextBox_0": "Isenção de responsabilidade", + "5_TextBox_1": "• 3D Slicer is a free open source software application distributed under a BSD style license. \n\n\n• The software is not FDA approved or CE-Marked, and is for research use only.\nTutorial Outline", + "6_TextBox_0": "Resumo do tutorial", + "6_TextBox_1": "• Part 1: Loading and Viewing DICOM data\n\n• Part 2: Volume Rendering\n\n\n• Part 3: Loading and Viewing 3D models", + "7_TextBox_0": "Part 1: DICOM Data Loading", + "8_LoadingaDICOMvolume_title": "Loading a DICOM volume", + "8_TextBox_0": "Slicer displays the user interface of the DICOM module", + "8_TextBox_1": "O estudo do paciente 1 contém um conjunto de dados de tomografia computadorizada de tórax e abdome", + "9_LoadingaDICOMvolume_title": "Loading a DICOM volume", + "9_ArrowText_1": "Select patient1 and click on Load \nto load the dataset in Slicer", + "10_VisualizingDICOMimages_title": "Visualizing DICOM images", + "10_TextBox_0": "Slicer exibe o axial, coronal\ne imagens sagitais da TC\nConjunto de dados Thorax Abdomen ", + "11_VisualizingDICOMimages_title": "Visualizing DICOM images", + "11_ArrowText_1": "Left click on DICOM to display \nthe list of modules of Slicer", + "11_ArrowText_2": "Select the module \nVolumes", + "12_VisualizingDICOMimages_title": "Visualizing DICOM images", + "12_ArrowText_0": "Click on the CT-abdomen \npreset to automatically adjust \nthe window/level display of the \nCT dataset", + "13_VisualizingDICOMimages_title": "Visualizing DICOM images", + "13_TextBox_1": "Position the mouse cursor \nover the red banner in the \nRed Viewer to display the slice \nmenu.\n\n\nClick on the Links icon to link \nthe slice controls across all \nSlice Viewers. \n\n\nClick on the Eye icon to\ndisplay the three anatomical \nslices in the 3D Viewer", + "14_VisualizingDICOMimages_title": "Visualizing DICOM images", + "14_TextBox_0": "The three anatomical slices \nappear in the 3D viewer.", + "15_VisualizingDICOMimages_title": "Visualizing DICOM images", + "15_ArrowText_0": "Click on the Slicer layout menu \nicon, and select the \nConventional Widescreen layout", + "16_VisualizingDICOMimages_title": "Visualizing DICOM images", + "16_TextBox_0": "O fatiador alterna o layout\npara Convencional\nLayout de tela ampla", + "17_VisualizingDICOMimages_title": "Visualizing DICOM images", + "17_TextBox_0": "Use o botão direito do mouse no\nVisualizador 3D para aumentar e diminuir o zoom", + "18_VisualizingDICOMimages_title": "Visualizing DICOM images", + "18_TextBox_0": "Use the left mouse button in the \n3D Viewer to rotate the images", + "19_3DViewerController_title": "3D Viewer Controller", + "19_TextBox_1": "Position the mouse cursor over \nthe pin icon in the blue banner \nof the 3D viewer window to \ndisplay the 3DView controller\n\nClick on the second icon on the \ntop row of the 3DView \ncontroller to center the 3D view \non the scene", + "20_3DViewerController_title": "3D Viewer Controller", + "20_ArrowText_1": "Select the Volume Rendering \nmodule in the list of modules ", + "21_TextBox_0": "Part 2: Volume Rendering", + "22_TextBox_0": "Volume Rendering", + "22_TextBox_1": "• Volume rendering \ntechniques enable 3D \nvisualization of 3D \ndatasets\n\n• The Volume Rendering \nmodule in Slicer enables \ninteractive 3D visualization \nof DICOM images", + "23_VolumeRendering_title": "Volume Rendering", + "23_ArrowText_0": "Clique em Predefinição na guia Exibir\ne selecione a predefinição CT-Cardiac3 ", + "24_VolumeRendering_title": "Volume Rendering", + "24_TextBox_2": "Select VTK GPU Ray Casting Rendering\nClick on the eye icon in the Volume tab to display \nthe volume rendered image in the 3D viewer", + "25_VolumeRendering_title": "Volume Rendering", + "25_ArrowText_0": "Use the shift slider to \nchange the transfer \nfunction and display the\naorta", + "26_VolumeRendering_title": "Volume Rendering", + "26_ArrowText_0": "Clique em Exibir ROI para\nmostrar uma região de interesse\n(ROI) no visualizador 3D e\nverificar a opção Habilitar", + "27_VolumeRendering_title": "Volume Rendering", + "27_TextBox_0": "Turn off the visibility of the \naxial, sagittal and coronal \nslices in the 2D viewer \n\n\nPosition the ROI around the \nleft kidney using the color \nhandles", + "28_VolumeRendering_title": "Volume Rendering", + "28_ArrowText_0": "Clique no ícone do olho para\nexibir o volume renderizado\nimagem", + "29_VolumeRendering_title": "Volume Rendering", + "29_TextBox_0": "Slicer displays the \nvolume rendered \nimage of the left kidney ", + "30_VolumeRendering_title": "Volume Rendering", + "30_TextBox_0": "Amplie a ROI para gerar\numa imagem renderizada em volume do\nrim direito", + "31_VolumeRendering_title": "Volume Rendering", + "31_ArrowText_1": "Click on File, then Close Scene\nin the main menu", + "32_TextBox_0": "Part 3: Loading and \nviewing 3D models\n", + "33_TextBox_0": "Tutorial dataset", + "33_TextBox_1": "• The directory dataset2_Head contains the Slicer scene called Head_scene.mrb\n\n• The scene contains 3D models from the SPL brain atlas developed by the department of Radiology at Brigham and Women’s Hospital, Harvard Medical School (NIH P41 RR013218, NIH R01 MH05074)", + "34_TextBox_0": "Cena do Slicer", + "34_TextBox_1": "Slicer stores all loaded data in a repository called a scene\n\n\nEach data set, such as an image volume, surface model, or point set, is represented as a node in a Slicer scene.\n\n\nAll Slicer modules operate on the data stored in a Slicer scene.", + "35_LoadingaScene_title": "Carregando uma cena", + "35_TextBox_0": "O Slicer exibe um modelo de \nsuperfície 3D da cabeça e cortes \nde ressonância magnética 2D", + "36_Viewing3Dmodels_title": "Viewing 3D models", + "36_ArrowText_0": "Posicione o cursor sobre\no ícone do pino para revelar o\nmenu de fatias e clique em\no ícone do olho para exibir\nfatia axial no espectador 3D", + "37_Viewing3Dmodels_title": "Viewing 3D models", + "37_ArrowText_1": "Select the Models module \nin the list of models", + "38_Viewing3Dmodels_title": "Viewing 3D models", + "38_ArrowText_0": "Lower the opacity of \nthe Skin model using \nthe visibility slider", + "38_TextBox_1": "The skull bone and \neyeballs models appear \nthrough the skin", + "39_Viewing3Dmodels_title": "Viewing 3D models", + "39_ArrowText_0": "Slicer displays the list of \n3D models loaded in the \nscene\n\nSelect the model Skin.vtk", + "40_Viewing3Dmodels_title": "Viewing 3D models", + "40_ArrowText_1": "Select the skull bone \nmodel and click on the \neye icon to turn off its \nvisibility", + "40_TextBox_2": "The white matter and \noptic nerve models \nappear through the skin", + "41_Interactingwith3Dmodels_title": "Interacting with 3D models", + "41_ArrowText_0": "Clique no ícone do olho para\nexibir o corte coronal\nno visualizador 3D", + "42_Interactingwith3Dmodels_title": "Interacting with 3D models", + "42_ArrowText_2": "Select the hemispheric \nwhite matter model and \nselect the option Clipping", + "43_Interactingwith3Dmodels_title": "Interacting with 3D models", + "43_TextBox_0": "Mova a fatia coronal\nposteriormente para exibir o\nquiasma óptico", + "44_Interactingwith3Dmodels_title": "Interacting with 3D models", + "44_TextBox_0": "O Slicer exibe uma visualização 3D do\nquiasma óptico", + "45_TextBox_0": "Conclusão", + "45_TextBox_1": "• 3D Slicer provides advanced functionalities for loading and viewing 3D medical imaging data\n\n• The tutorial demonstrates how to use volume \nrendering and 3D surface modeling for \ninteractive visualization of CT and MRI data\n\n\nContact: spujol@bwh.harvard.edu", + "46_TextBox_0": "Agradecimentos", + "46_TextBox_1": "Neuroimage Analysis Center (NIBIB P41 EB015902)" +} \ No newline at end of file