This study investigates the use of a 3D U-Net model for brain tumor segmentation utilizing the BraTS dataset, which includes multimodal MRI scans capturing critical tumor features such as edema and necrosis.
The proposed system employs a pre-trained 3D U-Net model to automate tumor detection, offering improved accuracy and efficiency compared to traditional methods. By integrating deep learning with advanced neuroimaging, this research aims to enhance diagnostic precision and support clinical decision-making in brain tumor management.
To know in detail about this research, visit my IEEE published research paper - https://ieeexplore.ieee.org/document/10961442
The Dataset used is avilable on Kaggle as named BRATS2020 datset. dataset Link- https://www.kaggle.com/datasets/awsaf49/brats20-dataset-training-validation
