mazurowski-lab/segmentation-guided-diffusion
[MICCAI 2024] Easy diffusion models (optionally with segmentation guidance) for medical images and beyond.
This tool helps medical researchers and practitioners generate realistic medical images, such as MRIs or CT scans, based on specific anatomical segmentations. You input existing segmentation masks (outlines of organs or structures) and it outputs new, synthetic medical images that precisely match those anatomical boundaries. This is especially useful for creating diverse datasets for training or research when real data is scarce or incomplete.
211 stars. No commits in the last 6 months.
Use this if you need to create high-fidelity synthetic medical images that adhere strictly to given anatomical segmentations, even if those segmentations are incomplete.
Not ideal if you're looking for a general-purpose image generation tool for non-medical images without specific segmentation guidance.
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211
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Language
Python
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Last pushed
Jun 18, 2025
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