aiforvision/OCTA-autosegmentation
Repository for the paper "Synthetic optical coherence tomography angiographs for detailed retinal vessel segmentation without human annotations" (2024).
This project helps medical researchers and clinicians automatically identify and segment tiny blood vessels in retinal OCTA images. It takes raw OCTA scans or generates synthetic ones, then outputs precise segmentations of the retinal vasculature. This is for ophthalmologists, neurologists, or cardiologists who analyze these images for disease diagnosis and biomarker extraction.
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Use this if you need accurate, automated segmentation of retinal blood vessels from OCTA images, especially the smallest capillaries, without relying on extensive manual annotations.
Not ideal if your primary need is general image processing or segmentation of non-retinal structures, or if you require segmentation of different image modalities.
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MIT
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Last pushed
Aug 11, 2025
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