analysiscenter/radio

RadIO is a library for data science research of computed tomography imaging

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Emerging

This project helps medical imaging researchers or data scientists working with computed tomography (CT) scans to efficiently process and analyze their image data. It takes raw CT scan files (like DICOM or MetaImage) and outputs prepared data suitable for training machine learning models, along with pre-built neural networks for tasks like cancer detection. The end-user is typically a medical imaging data scientist or researcher.

226 stars. No commits in the last 6 months.

Use this if you need to streamline the loading, preprocessing, and model training workflow for large datasets of CT scans, especially for tasks like classification or semantic segmentation.

Not ideal if you are looking for a clinical diagnostic tool or a simple image viewer, as this is focused on research and model development.

medical-imaging computed-tomography radiology-research medical-AI-development cancer-detection
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 22 / 25

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Stars

226

Forks

53

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Jan 21, 2022

Commits (30d)

0

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