Brainchop: In-browser MRI volumetric segmentation and rendering
Authors/Creators
- 1. Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)
- 2. Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), and Department of Computer Science, Georgia State University.
Description
Brainchop is a client-side web-application for automatic segmentation of MRI volumes that brings automatic volumetric segmentation capability to neuroimaging by running a robustly pre-trained deep learning model. The app does not require technical sophistication from the user and is designed for locally and privately segmenting user’s T1 volumes. Results of the segmentation may be easily saved locally after the computation. An intuitive interactive interface that does not require any special training nor specific instruction to run enables access to a state of the art deep learning brain segmentation for anyone with a modern browser (e.g. Firefox, Chrome etc) and commonly available hardware. Additionally, we make implementation of brainchop freely available releasing its pure Javascript code as open-source.
Online Demo: brainchop.org
Source: Github Repo
Doc: Github Wiki
For local setup please follow these instructions
In v2.1.0, brainchop code and paper revised as per Journal of Open Source Software (JOSS) reviewers requested.
Notes
Files
brainchop-v2.1.0.zip
Files
(148.7 MB)
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Additional details
Related works
- Is published in
- Journal article: 10.21105/joss.05098 (DOI)