black0017/MedicalZooPytorch

Health v2 · maintenance only

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Adoption not part of the score

1917 stars · 305 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch-based open-source library implementing state-of-the-art 3D (and some 2D) deep neural networks for multi-modal medical image segmentation, with data loaders for common medical imaging datasets like BraTS and MRBrains. It aims to support reproducible deep learning research in medical imaging, originally focused on 3D multi-modal brain MRI segmentation.

Use cases

• segment 3D brain MRI scans with deep learning
• train a U-Net on the BraTS tumor segmentation dataset
• run multi-modal medical image segmentation in PyTorch
• get data loaders for medical imaging challenge datasets
• compare 3D segmentation architectures like V-Net and UNet
• apply deep learning to medical image volumes

When to choose

• you need ready-made 3D segmentation architectures in PyTorch for medical images
• you are working with brain MRI datasets like BraTS, ISEG, or MRBrains
• you want reproducible baselines for medical image segmentation research

When to avoid

• you need general-purpose (non-medical) image segmentation
• you require production-grade clinical deployment tooling
• you need 2D-only lightweight segmentation models with broad dataset support

Facets

library · maturity maintenance

deep-learning machine-learning image-processing deep-learning machine-learning healthcare image-processing python medical-imaging image-segmentation pytorch 3d-segmentation mri brain-segmentation unet medical-image-dataloaders gpu

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