https://github.com/nitrain/tutorials
Examples and tutorials for training medical imaging AI models with nitrain
https://github.com/nitrain/tutorials
Last synced: 10 months ago
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Examples and tutorials for training medical imaging AI models with nitrain
- Host: GitHub
- URL: https://github.com/nitrain/tutorials
- Owner: nitrain
- Created: 2024-04-09T10:30:49.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-30T09:35:06.000Z (about 2 years ago)
- Last Synced: 2025-06-20T05:50:54.636Z (about 1 year ago)
- Language: Python
- Size: 2.26 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Tutorials and examples for nitrain
This repository contains full end-to-end tutorials and examples for the nitrain framework for medical imaging AI. They cover different types of imaging types (2D, 3D), tasks (classification, segmentation, regression), and frameworks (keras, pytorch).
If you are looking to learn more about training medical imaging AI models in general, then check out the book [Becoming a medical imaging AI expert with Python](https://book.nitrain.dev). An overview of the various tutorials available here is presented below.
- Introduction - using the nitrain framework [[Link](https://github.com/nitrain/tutorials/tree/main/introduction)]
- Segmentation - training medical image segmentation models with nitrain [[Link](https://github.com/nitrain/tutorials/tree/main/segmentation)]
- Classification - training models for classification with nitrain [[Link](https://github.com/nitrain/tutorials/tree/main/classification)]
- Registration - training models for image registration with nitrain [[Link](https://github.com/nitrain/tutorials/tree/main/registration)]
## Contributing
Please submit an issue if you have an example to contribute or want to request a specific tutorial, model, or dataset. We welcome all contributions and requests.