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RC-Net: Rethinking Region Consistency in Semi-supervised 3D Medical Image Segmentation

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RC-Net: Rethinking Region Consistency in Semi-supervised 3D Medical Image Segmentation

This repository contains the official implementation of RC-Net, proposed in our paper "Rethinking Region Consistency in Semi-supervised 3D Medical Image Segmentation".

Overview

RC-Net introduces a novel approach to improve weak-to-strong consistency methods, emphasizing the foreground-background paradigm to enhance segmentation performance, particularly in challenging medical imaging tasks. Our method effectively reduces edge uncertainty and improves robustness in texture-blurred scenarios.

Code Availability

The code for RC-Net will be made publicly available upon acceptance of the paper. Stay tuned for updates!

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RC-Net: Rethinking Region Consistency in Semi-supervised 3D Medical Image Segmentation

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