GitHub / abhiram4 / Multipass-3D-UNet-for-Pelvis-Segmentation

MultiPass U-Net is an advanced image segmentation model designed to iteratively refine predictions by running multiple passes through a U-Net architecture. Ideal for histopathology and medical imaging, it improves segmentation of fine structures and rare features by leveraging deep contextual learning across passes.

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PURL: pkg:github/abhiram4/Multipass-3D-UNet-for-Pelvis-Segmentation

Topics: medical-imaging, multipass, unet, unet-image-segmentation, unet-tensorflow

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