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Mmasoud1 committed May 18, 2024
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**Frontend For Neuroimaging. Open Source**

**[Demo](https://neuroneural.github.io/brainchop/v3)   [Updates](#Updates)   [Doc](https://github.com/neuroneural/brainchop/wiki/)   [News!](#News)   [Cite](#Citation)**
**[Demo](https://neuroneural.github.io/brainchop/v3)   [Doc](https://github.com/neuroneural/brainchop/wiki/)**

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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>.

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">

![Interface](./css/images/brainchop_Arch.png)

**Brainchop high-level architecture**
</div>


<div align="center">

![Interface](./css/images/DL_Arch.png)

**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.

* [![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)

* [![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)

<br>

## Live Demo

To see Brainchop v3.4.0 in action please click [here](https://neuroneural.github.io/brainchop/v3).

<br>

## Updates

<div align="center">

<img src="./css/images/BrainchopMoreRobustModels.gif" width="60%">

**Brainchop v3.0.0 with more robust models**
</div>

<br>


<div align="center">

![Interface](./css/images/Input3DEnhancements.gif)

**Brainchop v1.4.0 rendering MRI Nifti file in 3D**
</div>

<br>

<div align="center">

![Interface](./css/images/Brainchop3D.gif)


**Brainchop v1.3.0 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="./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="./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="./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="./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="./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="./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="./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) [![DOI](https://joss.theoj.org/papers/10.21105/joss.05098/status.svg)](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>
> **Note:** The remaining content of this README file has been moved to the main [README.md](../README.md) file in the root of the repository. Please refer to the main README for general information, last updates, news, citations, usage guidelines, and contribution details.
## Funding

This work was funded by the NIH grant RF1MH121885. Additional support from NIH R01MH123610, R01EB006841 and NSF 2112455.

<br />
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