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MIT License | ||
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Copyright (c) 2021 neuroneural/brainchop | ||
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Permission is hereby granted, free of charge, to any person obtaining a copy | ||
of this software and associated documentation files (the "Software"), to deal | ||
in the Software without restriction, including without limitation the rights | ||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | ||
copies of the Software, and to permit persons to whom the Software is | ||
furnished to do so, subject to the following conditions: | ||
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The above copyright notice and this permission notice shall be included in all | ||
copies or substantial portions of the Software. | ||
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | ||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | ||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | ||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | ||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | ||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | ||
SOFTWARE. |
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# Brainchop [![Version](https://img.shields.io/badge/Version-2.1.0-brightgreen)]() [![JS ](https://img.shields.io/badge/Types-JavaScript-blue)]() [![MIT-License ](https://img.shields.io/badge/license-MIT-green)](https://github.com/neuroneural/brainchop/blob/master/LICENSE) [![tfjs](https://img.shields.io/badge/tfjs-Pre--trained%20Model-blue)](https://github.com/neuroneural/brainchop/tree/master/models/mnm_tfjs_me_test) [![DOI](https://joss.theoj.org/papers/10.21105/joss.05098/status.svg)](https://doi.org/10.21105/joss.05098) | ||
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<div align="center"> | ||
<a href="https://neuroneural.github.io/brainchop"> | ||
<img width="100%" src="https://github.com/neuroneural/brainchop/blob/master/css/images/Banner.png"> | ||
</a> | ||
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**Frontend For Neuroimaging. Open Source** | ||
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**[Demo](https://neuroneural.github.io/brainchop)   [Updates](#Updates)   [Doc](https://github.com/neuroneural/brainchop/wiki/)   [News!](#News)   [Cite](#Citation)** | ||
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</div> | ||
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<br> | ||
<img src="https://github.com/neuroneural/brainchop/blob/master/css/logo/brainchop_logo.png" width="25%" align="right"> | ||
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<p align="justify"> | ||
<b><a href="https://neuroneural.github.io/brainchop/" style="text-decoration: none"> Brainchop</a></b> brings automatic 3D MRI volumetric segmentation capability to neuroimaging by running a lightweight deep learning model (e.g., <a href="https://medium.com/pytorch/catalyst-neuro-a-3d-brain-segmentation-pipeline-for-mri-b1bb1109276a" target="_blank" style="text-decoration: none"> MeshNet</a>) in the web-browser for inference on the user side. | ||
</p> | ||
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<p align="justify"> | ||
We make the implementation of Brainchop freely available, releasing its pure javascript code as open-source. The user interface (UI) provides a web-based end-to-end solution for 3D MRI segmentation. <b><a href="https://rii-mango.github.io/Papaya/" style="text-decoration: none">Papaya</a></b> viewer is integrated with the tool for MRI visualization. In version 1.3.0, <b><a href="https://threejs.org/" style="text-decoration: none">Three.js</a></b> is used for MRI 3D rendering. For more information about Brainchop, please refer to this detailed <b><a href="https://github.com/neuroneural/brainchop/wiki/" style="text-decoration: none">Wiki</a></b> and this <b><a href="https://trendscenter.org/in-browser-3d-mri-segmentation-brainchop-org/" style="text-decoration: none"> Blog</a></b>. | ||
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For questions or to share ideas, please refer to our <b><a href="https://github.com/neuroneural/brainchop/discussions/" style="text-decoration: none"> Discussions </a></b> board. | ||
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</p> | ||
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<div align="center"> | ||
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![Interface](https://github.com/neuroneural/brainchop/blob/master/css/images/brainchop_Arch.png) | ||
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**Brainchop high-level architecture** | ||
</div> | ||
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<div align="center"> | ||
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![Interface](https://github.com/neuroneural/brainchop/blob/master/css/images/DL_Arch.png) | ||
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**MeshNet deep learning architecture used for inference with Brainchop** (MeshNet <a href="https://arxiv.org/pdf/1612.00940.pdf" target="_blank" style="text-decoration: none"> paper</a>) | ||
</div> | ||
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## MeshNet Example | ||
This basic example provides an overview of the training pipeline for the MeshNet model. | ||
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* [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuroneural/brainchop/blob/master/py2tfjs/MeshNet_Training_Example.ipynb) [MeshNet basic training example](./py2tfjs/MeshNet_Training_Example.ipynb) | ||
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* [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuroneural/brainchop/blob/master/py2tfjs/Convert_Trained_Model_To_TFJS.ipynb) [Convert the trained MeshNet model to tfjs model example ](./py2tfjs/Convert_Trained_Model_To_TFJS.ipynb) | ||
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<br> | ||
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## Live Demo | ||
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To see Brainchop in action please click [here](https://neuroneural.github.io/brainchop). | ||
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<br> | ||
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## Updates | ||
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<div align="center"> | ||
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<img src="https://github.com/neuroneural/brainchop/blob/master/css/images/BrainchopMoreRobustModels.gif" width="60%"> | ||
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**Brainchop v3.0.0 with more robust models** | ||
</div> | ||
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<br> | ||
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<div align="center"> | ||
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![Interface](https://github.com/neuroneural/brainchop/blob/master/css/images/Input3DEnhancements.gif) | ||
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**Brainchop v1.4.0 rendering MRI Nifti file in 3D** | ||
</div> | ||
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<br> | ||
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<div align="center"> | ||
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![Interface](https://github.com/neuroneural/brainchop/blob/master/css/images/Brainchop3D.gif) | ||
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**Brainchop v1.3.0 rendering segmentation output in 3D** | ||
</div> | ||
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## News! | ||
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* Brainchop [v2.2.0](https://github.com/neuroneural/brainchop/releases/tag/v2.2.0) paper is accepted in the 21st IEEE International Symposium on Biomedical Imaging ([ISBI 2024](https://biomedicalimaging.org/2024/)). Lengthy arXiv version can be found [here](https://arxiv.org/abs/2310.16162). | ||
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<div align="center"> | ||
<img src="https://github.com/neuroneural/brainchop/blob/master/css/news/ISBI_2024.jpeg" width="40%"> | ||
</div> | ||
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<br> | ||
<br> | ||
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* Brainchop [paper](https://doi.org/10.21105/joss.05098) is published in the Journal of Open Source Software (JOSS) on March 28, 2023. | ||
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<div align="center"> | ||
<a href="https://doi.org/10.21105/joss.05098"><img src="https://github.com/neuroneural/brainchop/blob/master/css/news/JOSS_Logo.png"></a> | ||
</div> | ||
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<br> | ||
<br> | ||
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* Brainchop abstract is accepted for poster presentation during the 2023 [OHBM](https://www.humanbrainmapping.org/) Annual Meeting. | ||
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<div align="center"> | ||
<img src="https://github.com/neuroneural/brainchop/blob/master/css/news/OHBM_2023.jpeg" width="40%"> | ||
</div> | ||
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<br> | ||
<br> | ||
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* Brainchop 1-page abstract and poster is accepted in 20th IEEE International Symposium on Biomedical Imaging ([ISBI 2023](https://2023.biomedicalimaging.org/en/)) | ||
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<div align="center"> | ||
<img src="https://github.com/neuroneural/brainchop/blob/master/css/news/ISBI_2023.png" width="40%"> | ||
</div> | ||
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<br> | ||
<br> | ||
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* Google, Tensorflow community spotlight award for brainchop (Sept 2022) on [Linkedin](https://www.linkedin.com/posts/tensorflow-community_github-neuroneuralbrainchop-brainchop-activity-6978796859532181504-cfCW?utm_source=share&utm_medium=member_desktop) and [Twitter](https://twitter.com/TensorFlow/status/1572980019999264774) | ||
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<div align="center"> | ||
<img src="https://github.com/neuroneural/brainchop/blob/master/css/news/TF_CommunityAward.png" width="60%"> | ||
</div> | ||
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<br> | ||
<br> | ||
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* Brainchop invited to [Pytorch](https://pytorch.org/ecosystem/ptc/2022) flag conference, New Orleans, Louisiana (Dec 2022) | ||
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<div align="center"> | ||
<img src="https://github.com/neuroneural/brainchop/blob/master/css/news/Pytorch_Poster.jpg" width="50%"> | ||
</div> | ||
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<br> | ||
<br> | ||
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* Brainchop invited to TensorFlow.js Show & Tell episode #7 (Jul 2022). | ||
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<div align="center"> | ||
<img src="https://github.com/neuroneural/brainchop/blob/master/css/news/TF_show_tell.png" width="50%"> | ||
</div> | ||
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## Citation | ||
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Brainchop [paper](https://doi.org/10.21105/joss.05098) for v2.1.0 is published on March 28, 2023, in the Journal of Open Source Software (JOSS) [![DOI](https://joss.theoj.org/papers/10.21105/joss.05098/status.svg)](https://doi.org/10.21105/joss.05098) | ||
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<br> | ||
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For **APA** style, the paper can be **cited** as: | ||
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> Masoud, M., Hu, F., & Plis, S. (2023). Brainchop: In-browser MRI volumetric segmentation and rendering. Journal of Open Source Software, 8(83), 5098. https://doi.org/10.21105/joss.05098 | ||
<br> | ||
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For **BibTeX** format that is used by some publishers, please use: | ||
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```BibTeX: | ||
@article{Masoud2023, | ||
doi = {10.21105/joss.05098}, | ||
url = {https://doi.org/10.21105/joss.05098}, | ||
year = {2023}, | ||
publisher = {The Open Journal}, | ||
volume = {8}, | ||
number = {83}, | ||
pages = {5098}, | ||
author = {Mohamed Masoud and Farfalla Hu and Sergey Plis}, | ||
title = {Brainchop: In-browser MRI volumetric segmentation and rendering}, | ||
journal = {Journal of Open Source Software} | ||
} | ||
``` | ||
<br> | ||
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For **MLA** style: | ||
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> Masoud, Mohamed, Farfalla Hu, and Sergey Plis. ‘Brainchop: In-Browser MRI Volumetric Segmentation and Rendering’. Journal of Open Source Software, vol. 8, no. 83, The Open Journal, 2023, p. 5098, https://doi.org10.21105/joss.05098. | ||
<br> | ||
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For **IEEE** style: | ||
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> M. Masoud, F. Hu, and S. Plis, ‘Brainchop: In-browser MRI volumetric segmentation and rendering’, Journal of Open Source Software, vol. 8, no. 83, p. 5098, 2023. doi:10.21105/joss.05098 | ||
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<br> | ||
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## Funding | ||
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This work was funded by the NIH grant RF1MH121885. Additional support from NIH R01MH123610, R01EB006841 and NSF 2112455. | ||
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<br /> | ||
<div align="center"> | ||
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<img src='https://github.com/neuroneural/brainchop/blob/master/css/logo/TReNDS_logo.jpg' width='300' height='100'></img> | ||
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**Mohamed Masoud - Sergey Plis - 2024** | ||
</div> |
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