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https://github.com/nitrain/book
Source code for the book "Becoming a medical imaging AI expert with Python" (expected early 2025)
https://github.com/nitrain/book
Last synced: about 1 month ago
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Source code for the book "Becoming a medical imaging AI expert with Python" (expected early 2025)
- Host: GitHub
- URL: https://github.com/nitrain/book
- Owner: nitrain
- License: other
- Created: 2024-04-10T09:25:04.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-04-13T10:49:55.000Z (9 months ago)
- Last Synced: 2024-04-14T05:44:01.257Z (8 months ago)
- Language: Jupyter Notebook
- Homepage: https://book.nitrain.dev
- Size: 2.76 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
README
# Practical medical imaging AI techniques with Python
This book will take you through the entire medical imaging AI workflow from data to deployment using the nitrain framework and pytorch. A final published draft is expected in early 2025.
The book is publically available at [book.nitrain.dev](https://book.nitrain.dev).
## About the book
By going through this book, you will learn how to tackle any medical imaging AI problem in Python. That includes building regression, classification, or image-to-image models for any type of medical imaging processing task. It is split up into multiple parts that operate more-or-less independently in case you want to sharpen your skills in one particular area.
## About the author
Nicholas Cullen has a BS in Systems Engineering from University of Florida and a PhD in Biostatistics from Lund University in Sweden. He has 10+ years of experience developing tools for medical imaging in Python, R, and C++. He has published 40+ high-impact journal articles on biomarkers, clinical trials, and neurodegenerative diseases.
He started nitrain to make medical imaging AI more accessible to clinical researchers. If you have any questions, he can be reached at [email protected].
## Credits
This project is created using the excellent open source [Jupyter Book project](https://jupyterbook.org/) and the [executablebooks/cookiecutter-jupyter-book template](https://github.com/executablebooks/cookiecutter-jupyter-book).