Brainchop: Next Generation Web-Based Neuroimaging Application

TL;DR

Brainchop is a pioneering web-based neuroimaging application that performs volumetric MRI analysis using deep learning models directly in the browser, ensuring data privacy and accessibility without complex setup.

Contribution

It introduces a novel in-browser neuroimaging tool that enables end-to-end brain MRI processing with deep learning, overcoming browser environment limitations.

Findings

Client-side processing is practical for volumetric MRI analysis.

MeshNet architecture enables efficient deep learning in browsers.

The tool offers scalable, low-latency neuroimaging analysis accessible to non-experts.

Abstract

Performing volumetric image processing directly within the browser, particularly with medical data, presents unprecedented challenges compared to conventional backend tools. These challenges arise from limitations inherent in browser environments, such as constrained computational resources and the availability of frontend machine learning libraries. Consequently, there is a shortage of neuroimaging frontend tools capable of providing comprehensive end-to-end solutions for whole brain preprocessing and segmentation while preserving end-user data privacy and residency. In light of this context, we introduce Brainchop (http://www.brainchop.org) as a groundbreaking in-browser neuroimaging tool that enables volumetric analysis of structural MRI using pre-trained full-brain deep learning models, all without requiring technical expertise or intricate setup procedures. Beyond its commitment to data privacy, this frontend tool offers multiple features, including scalability, low latency, user-friendly operation, cross-platform compatibility, and enhanced accessibility. This paper outlines the processing pipeline of Brainchop and evaluates the performance of models across various software and hardware configurations. The results demonstrate the practicality of client-side processing for volumetric data, owing to the robust MeshNet architecture, even within the resource-constrained environment of web browsers.