risc-mi/braintumor-ddpm
Using learned visual representations from diffusion models for brain tumor segmentation.
This project helps medical professionals efficiently identify and outline brain tumors on MRI scans. It takes axial slices of brain MRI images and automatically outputs segmented maps highlighting tumor regions. Radiologists and neurologists can use this to quickly get preliminary tumor segmentations, especially when only a few examples are available.
No commits in the last 6 months.
Use this if you need to segment brain tumors from MRI scans with very limited training data, as it outperforms traditional supervised methods in low-data scenarios.
Not ideal if you require highly accurate segmentations for out-of-distribution slices that are significantly different from the training examples.
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Language
Python
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Last pushed
Jul 20, 2023
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