Yebulabula/DisC-Diff
【MICCAI 2023, Early accept】DisC-Diff: Disentangled Conditional Diffusion Model for Multi-Contrast MRI Super-Resolution
This project helps medical professionals and researchers enhance the detail of multi-contrast brain MRI scans. It takes low-resolution T1 and T2 weighted MRI images and outputs higher-resolution versions, revealing finer anatomical structures. Radiologists, neurologists, and medical imaging researchers can use this to improve diagnostic clarity or analysis without needing to re-scan patients.
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Use this if you need to generate high-resolution brain MRI images from existing low-resolution multi-contrast T1 and T2 scans.
Not ideal if you are working with single-contrast MRI, other imaging modalities like CT or X-ray, or need to process non-brain anatomical regions.
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52
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4
Language
Python
License
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Last pushed
Jun 06, 2023
Commits (30d)
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