Web-App Overview
This application is a browser-based prototype for an interactive histopathology analysis tool. It allows users to explore, visualize, and simulate the processing of high-resolution tissue images directly within the browser. All operations are performed client-side, ensuring data privacy and speed without requiring any server-side infrastructure, plugins, or installations.
How To Use
- Select Sample: Use the dropdown menu to choose from a set of pre-defined synthetic tissue samples.
- Navigate the Image:
- Zoom: Use the mouse wheel or a two-finger pinch gesture on touch devices.
- Pan: Click and drag with the mouse or use a one-finger drag on touch devices.
- Choose Analysis: Select an analysis mode like "Cell Counting" or "Tumor Segmentation" from the second dropdown. The analysis will run automatically.
- Adjust Parameters (On-the-fly): Use the sliders to control parameters. The primary analysis slider (e.g., "Sensitivity", "Proximity") will update the analysis in real-time. It will be disabled if not applicable to the current mode.
- Toggle Overlays: Use the "Show Overlays" switch to hide or show the analysis results without re-running the process.
- Sonification: Enable the "Enable Sound" switch to hear auditory feedback corresponding to the analysis.
- Play Demo: Click the "Play Demo" button to see an automated tour of the tool's features. The demo starts automatically after 10 seconds of inactivity and stops when you interact with the page.
Technical Details
- Single-File Architecture: The entire application (HTML, CSS, JavaScript, and data) is contained within this single file for maximum portability and simplicity.
- Client-Side Processing: All image rendering and analysis simulations are performed by JavaScript running in your browser. No data ever leaves your computer.
- Canvas Rendering: The tool uses two stacked HTML5
<canvas> elements. One renders the base image, and the other renders the analysis overlays. This improves performance by separating static and dynamic content.
- Synthetic Data: To avoid loading large image files and to keep the app self-contained, the histopathology "images" are procedurally generated from a JSON object embedded in the code.
- Interaction Model: The application supports mouse (wheel for zoom, drag for pan) and touch events (pinch for zoom, drag for pan).
- Sonification: The Web Audio API is used to generate simple sounds based on analysis results, providing multi-modal feedback.
- No Dependencies: The project is built with vanilla JavaScript, HTML, and CSS, without relying on any external frameworks.
Future Directions
This prototype serves as a foundation for a more powerful tool. Future enhancements could include:
- Real Image Support: Integration with libraries like OpenSeadragon to handle real, gigapixel-sized Whole Slide Images (WSIs).
- Machine Learning Integration: The modular analysis pipeline is designed to allow for the future integration of client-side machine learning models (using TensorFlow.js or ONNX.js) for more sophisticated, AI-driven analysis.
- Advanced Annotation Tools: Adding tools for users to manually draw regions of interest (ROIs), add labels, and correct automated analysis results.
- Data Export: Allowing users to export analysis results (e.g., cell counts, region areas) as a CSV or JSON file.
- 3D Visualization: Support for viewing and analyzing 3D imaging data, such as from confocal microscopy or serial sectioning.