ImageJS: Personalized, participated, pervasive, and reproducible image bioinformatics in the web browser

Area of Science:

• Bioinformatics
• Computational Biology
• Medical Imaging

Background:

• Traditional image bioinformatics relies on server-side computing and desktop applications, limiting collaborative ecosystems.
• Existing infrastructure struggles to support self-sustained, user-driven computational environments for image analysis.

Purpose of the Study:

• To develop a novel browser-based web application for image bioinformatics.
• To overcome the limitations of server-client models and promote open, collaborative research.

Main Methods:

• ImageJS was developed as a server-independent web application utilizing modern browser capabilities.
• Code migration via script tags was employed for deploying image analysis modules, contrasting with traditional data transfer methods.

Main Results:

• ImageJS modules for segmentation, feature extraction, and filtering were developed and deployed using versioned code hosting services.
• Code migration demonstrated reproducibility and provenance, offering advantages over data transfer for image analysis.

Conclusions:

• Modern web browsers are advantageous for image bioinformatics in research and clinical settings.
• ImageJS offers improved deployment scalability, analysis reproducibility, and secure delivery of computational procedures without local installation.