3D U-Net Convolution Neural Network

[Update August 2023 - data loading is now 10x faster!]

• Tutorials
• Introduction
• Quick Start Guide
  • Installation
  • Example
• Documentation
• Citation

Tutorials <a name="tutorials"></a>

Brain Tumor Segmentation (BraTS 2020)

Introduction <a name="introduction"></a>

We designed 3DUnetCNN to make it easy to apply and control the training and application of various deep learning models to medical imaging data. The links above give examples/tutorials for how to use this project with data from various MICCAI challenges.

Quick Start Guide <a name="quickstart"></a>

How to train a UNet on your own data.

Installation <a name="installation"></a>

1. Clone the repository:<br /> git clone https://github.com/ellisdg/3DUnetCNN.git <br /><br />

2. Install the required dependencies^*:<br /> pip install -r 3DUnetCNN/requirements.txt

^*It is highly recommended that an Anaconda environment or a virtual environment is used to manage dependcies and avoid conflicts with existing packages.

Create configuration file and run training <a name="brats2020"></a>

See the Brats 2020 example for a description on how to create a configuration and train a model.

Documentation <a name="documentation"></a>

• Configuration Guide
• Frequently Asked Questions

Still have questions? <a name="questions"></a>

Once you have reviewed the documentation, feel free to raise an issue on GitHub, or email me at david.ellis@unmc.edu.

Citation <a name="citation"></a>

Ellis D.G., Aizenberg M.R. (2021) Trialing U-Net Training Modifications for Segmenting Gliomas Using Open Source Deep Learning Framework. In: Crimi A., Bakas S. (eds) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2020. Lecture Notes in Computer Science, vol 12659. Springer, Cham. https://doi.org/10.1007/978-3-030-72087-2_4

Additional Citations

Ellis D.G., Aizenberg M.R. (2020) Deep Learning Using Augmentation via Registration: 1st Place Solution to the AutoImplant 2020 Challenge. In: Li J., Egger J. (eds) Towards the Automatization of Cranial Implant Design in Cranioplasty. AutoImplant 2020. Lecture Notes in Computer Science, vol 12439. Springer, Cham. https://doi.org/10.1007/978-3-030-64327-0_6

Ellis, D.G. and M.R. Aizenberg, Structural brain imaging predicts individual-level task activation maps using deep learning. bioRxiv, 2020: https://doi.org/10.1101/2020.10.05.306951