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--- a +++ b/README.md @@ -0,0 +1,240 @@ + +# Brainchop []() []() [](https://github.com/neuroneural/brainchop/blob/master/LICENSE) [](https://github.com/neuroneural/brainchop/tree/master/models/mnm_tfjs_me_test) [](https://doi.org/10.21105/joss.05098) + + +<div align="center"> + <a href="https://neuroneural.github.io/brainchop"> + <img width="100%" src="https://github.com/neuroneural/brainchop/releases/download/v3.4.0/Banner.png"> + </a> + + +**Frontend For Neuroimaging. Open Source** + +**[brainchop.org](https://neuroneural.github.io/brainchop)   [Updates](#Updates)   [Doc](https://github.com/neuroneural/brainchop/wiki/)   [News!](#News)   [Cite](#Citation)   [v3](https://neuroneural.github.io/brainchop/v3)** + +</div> + + +<br> + <img src="https://github.com/neuroneural/brainchop/blob/master/css/logo/brainchop_logo.png" width="25%" align="right"> + + <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> + + <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="v" style="text-decoration: none">NiiVue</a></b> viewer is integrated with the tool for MRI visualization. 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>. + + 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. + + </p> + +<div align="center"> + + + +**Brainchop high-level architecture** +</div> + + +<div align="center"> + + + +**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> + + +## MeshNet Example +This basic example provides an overview of the training pipeline for the MeshNet model. + +* [](https://colab.research.google.com/github/neuroneural/brainchop/blob/master/py2tfjs/MeshNet_Training_Example.ipynb) [MeshNet basic training example](./py2tfjs/MeshNet_Training_Example.ipynb) + +* [](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) + +<br> + +## Live Demo + +To see Brainchop **v4** in action please click [here](https://neuroneural.github.io/brainchop). Or click on the gif below to see a video: +<div align="center"> + +[](https://github.com/neuroneural/brainchop/releases/download/v4.1.0/Brainchop_overhaul.mp4) +</div> + +For **v3** click [here](https://neuroneural.github.io/brainchop/v3). + +<br> + + + +## Updates + +<div align="center"> + + <img src="https://github.com/neuroneural/brainchop/releases/download/v4.0.0/Brainchop_Niivue.png" width="100%"> + +**Brainchop <a href= "https://neuroneural.github.io/brainchop/" target="_blank" style="text-decoration: none"> v4 </a> with <a href= "https://github.com/niivue/niivue" target="_blank" style="text-decoration: none"> NiiVue</a> viewer** +</div> + +<br> + +<div align="center"> + + <img src="https://github.com/neuroneural/brainchop/releases/download/v3.4.0/BrainchopMoreRobustModels.gif" width="60%"> + +**Brainchop <a href= "https://neuroneural.github.io/brainchop/v3" target="_blank" style="text-decoration: none"> v3 </a> with more robust models** +</div> + +<br> + + +<div align="center"> + + + +**Brainchop <a href= "https://neuroneural.github.io/brainchop/v3" target="_blank" style="text-decoration: none"> v1.4.0 - v3.4.0 </a> rendering MRI Nifti file in 3D** +</div> + +<br> + +<div align="center"> + + + + +**Brainchop <a href= "https://neuroneural.github.io/brainchop/v3" target="_blank" style="text-decoration: none"> v1.3.0 - v3.4.0 </a> rendering segmentation output in 3D** +</div> + + + + + +## News! + +* 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). + +<div align="center"> + <img src="https://github.com/neuroneural/brainchop/blob/master/css/news/ISBI_2024.jpeg" width="40%"> +</div> + +<br> +<br> + +* Brainchop [paper](https://doi.org/10.21105/joss.05098) is published in the Journal of Open Source Software (JOSS) on March 28, 2023. + +<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> + +<br> +<br> + +* Brainchop abstract is accepted for poster presentation during the 2023 [OHBM](https://www.humanbrainmapping.org/) Annual Meeting. + +<div align="center"> + <img src="https://github.com/neuroneural/brainchop/blob/master/css/news/OHBM_2023.jpeg" width="40%"> +</div> + +<br> +<br> + +* Brainchop 1-page abstract and poster is accepted in 20th IEEE International Symposium on Biomedical Imaging ([ISBI 2023](https://2023.biomedicalimaging.org/en/)) + +<div align="center"> + <img src="https://github.com/neuroneural/brainchop/blob/master/css/news/ISBI_2023.png" width="40%"> +</div> + +<br> +<br> + +* 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) + +<div align="center"> + <img src="https://github.com/neuroneural/brainchop/blob/master/css/news/TF_CommunityAward.png" width="60%"> +</div> + +<br> +<br> + +* Brainchop invited to [Pytorch](https://pytorch.org/ecosystem/ptc/2022) flag conference, New Orleans, Louisiana (Dec 2022) + +<div align="center"> + <img src="https://github.com/neuroneural/brainchop/blob/master/css/news/Pytorch_Poster.jpg" width="50%"> +</div> + + +<br> +<br> + +* Brainchop invited to TensorFlow.js Show & Tell episode #7 (Jul 2022). + +<div align="center"> + <img src="https://github.com/neuroneural/brainchop/blob/master/css/news/TF_show_tell.png" width="50%"> +</div> + +## Citation + +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) [](https://doi.org/10.21105/joss.05098) + + +<br> + +For **APA** style, the paper can be **cited** as: + +> 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> + +For **BibTeX** format that is used by some publishers, please use: + +```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> + +For **MLA** style: + +> 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> + +For **IEEE** style: + +> 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 + + +<br> + +## Contribution and Authorship Guidelines + +If you modify or extend Brainchop in a derivative work intended for publication (such as a research paper or software tool), please cite and acknowledge the original Brainchop project and the original authors. Proper acknowledge should include the following: + +> **"Brainchop, originally developed by Mohamed Masoud and Sergey Plis (2023), was used in the development of this work."** + +We also request that significant contributions to derivative works be recognized by including original authors as co-authors, where appropriate. + +<br> + +## Funding + +This work was funded by the NIH grant RF1MH121885. Additional support from NIH R01MH123610, R01EB006841 and NSF 2112455. + +<br /> +<div align="center"> + +<img src='https://github.com/neuroneural/brainchop/blob/master/css/logo/TReNDS_logo.jpg' width='300' height='100'></img> + +**Mohamed Masoud - Sergey Plis - 2024** +</div>