Nexus Annotator

A Pathologist-Focused Cloud-ready Platform for AI-Assisted Ground-Truth Generation

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🚀 Overview

Nexus Annotator is a cloud-first digital annotation platform purpose-built for computational pathology workflows.
Designed in collaboration with pathologists, it streamlines ground-truth dataset generation by integrating AI-assisted region pre-selection, consensus-driven labeling, and customizable schema definitions for diverse renal disease cohorts.

Unlike traditional desktop tools that require complex installation, Nexus Annotator operates entirely in the browser, providing a scalable, collaborative environment for multi-institutional use.
It integrates with the Computational Renal Pathology Suite (CompRePS) to leverage open-source ML models for pre-identifying regions of interest (ROIs), enabling experts to focus on annotation quality rather than manual navigation.

The platform is currently being used to generate datasets for Focal Segmental Glomerulosclerosis (FSGS), Diabetic Nephropathy (DN) and Transplant (TX) cohorts.

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🧩 Core Architecture

Main Entrypoint — app.py

The app.py file is the central entrypoint for the application.
All new components to be added, pages, and cohort schemas are defined here.

Main things that operate here include:

• Adding new disease cohort data schemas and new application components
• Managing schema definitions and storage paths and database initializations.
• Integrating each annotation page under the Visualization class’s component dictionary

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Application Structure

All visualization and annotation modules are configured under the Visualization class as a components dictionary.
Each unique key:value pair under components represents an independent page in the Nexus Annotator application.

Example Configuration for a page

"DN Labels": [
    [
        (
            SlideMap(task_identifier=task_identifiers['DN']),
            {'width': '3'}
        ),
        (
            [
                FeatureAnnotation(
                    preset_schema=dn_feature_schema,
                    annotations_format='rgb',
                    labels_format='json',
                    storage_path=os.getenv('STORAGE_PATH','/pubapps/athena/fstools/localannotations/dn/'),
                    task_identifier=task_identifiers['DN']
                )
            ],
            {'width': '9'}
        )
    ]
]

This configuration defines a “DN Labels” page with:

A WSI viewer (SlideMap component) occupying 3 of 12 UI grid columns

A FeatureAnnotation panel occupying the remaining 9 columns

A data scheme (described below) and task identifier tied to the Diabetic Nephropathy cohort to uniquely identify the dataset and isolate them in the database.

🧬 Schema Design

Schemas define the annotation structure, field types, and layout for each cohort. A schema specifies what identifiers is collected and how it appears in the UI.

Example Schema

{
    "labels": [
        {
            "name": "Microaneurysm",
            "type": "checkbox",
            "options": ["Cellular", "Acellular"],
            "order": "COL1"
        }
    ]
}

📋 Supported Field Types

Type	Description
checkbox	Multiple selectable options
radio	Mutually exclusive selection
text	Single-line input
textarea	Multi-line comments or observations

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🧱 Layout & Column Control

• Supports two-column or three-column layouts
• Column placement via COL1, COL2, COL3
• If unspecified, defaults to a two-column evenly split layout

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🧠 UI and Layout System

Nexus Annotator uses a 12-column responsive layout system inspired by modern web design frameworks.

Each UI component is defined as a tuple:

(component, {'width': '<number_of_columns>'})
SlideMap: { 'width': '3' }
FeatureAnnotation: { 'width': '9' }

This ensures flexible, pixel-perfect layouts that scale across devices and resolutions.

🔐 Access Control

Access control is handled within the Dataset Builder component through two defined modes:

python
access_level_def: UserCollectionAccessLevel = {
    "ONLY_USER_FOLDER": "ONLY_USER_FOLDER",
    "ALL_USER_FOLDERS": "ALL_USER_FOLDERS"
}

Mode	Description
ONLY_USER_FOLDER	Displays only data in the user’s folder
ALL_USER_FOLDERS	Shows all accessible datasets (for admins or reviewers)

This structure ensures appropriate data visibility across users, institutions, and collaborative research groups.

🗄 Database and Data Persistence

Nexus Annotator includes a database integration layer that ensures:

• Persistent data across sessions

• Secure storage of all annotations, metadata, and schemas

• Synchronized progress tracking across users

• Each annotation event is logged and versioned to maintain dataset integrity for downstream AI training and validation.

🧰 Platform Features

🔑 1. Login & Authentication

• Authentication is managed through the connected Digital Slide Archive (DSA) instance (e.g., Athena).

• Users must be registered and approved in DSA to access Nexus Annotator.

🧾 2. Data Management

• Datasets are managed through the DSA.

• Users are currently required to maintain personal folders specific to the disease cohort in the user folder for efficient data organization.

🧩 3. Annotation Pages

• Each data cohort (e.g., DN, FSGS) corresponds to a dedicated annotation page.

• Page definitions and schemas are configured in app.py.

🧮 4. Annotation Filters

• Annotation files can be filtered by dataset type or annotation criteria.

• Filtering logic is implemented in segmentation.py within the components folder.

• Annotation file names must match those in Athena for synchronization.

📊 5. Progress Tracking

Two levels of progress indicators are built in:

Level	Description
Slide-level tracking	Reflects completion percentage for all required annotation files for a given slide
File-level tracking	Displays (completed annotations) / (total annotations) for each file

Progress values auto-refresh every 10 seconds (configurable).

🧭 6. Intelligent Navigation

• “Next” and “Previous” buttons to traverse ROIs

• Direct jump input for ROI index navigation

• The WSI viewer automatically follows the selected ROI

🧾 7. Label Submission

• After completing all ROI annotations for a file, users must click Submit Labels to finalize and export the data for downstream modeling workflows.

🧍 8. Reference Image Panel (Optional)

• A dedicated panel can display exemplar reference images to align annotators’ understanding and reduce inter-observer variability.

⚙️ Deployment Notes

Deployment is already setup and nothing needs to be modified except for a few environment variables that needs to be switched. Ensure that

• All storage paths in FeatureAnnotation components are correctly mounted

• Environment variable STORAGE_PATH is configured in the runtime environment

• File system permissions allow read/write access to annotation directories

Example:

bash
export STORAGE_PATH=/pubapps/athena/fstools/localannotations/dn/

Take a copy of the existing db file into the backup folder before every deployment and maintian version with different Docker tags to easily revert back to the previous stable application version.

🧩 Sample Development Workflow for new additions

Create a new schema for the desired cohort in app.py (can be separated to a different file).

Register the schema in app.py under the Visualization class

Define the page layout components avialble under the Visualization class

Specify task_identifiers for dataset separation and database addition.

Run locally and verify:

• UI rendering

• Schema mapping

• Database operations

License

nexus annotator was created by Suhas Katari Chaluva Kumar. It is licensed under the terms of the Apache 2.0 License