Web: http://arxiv.org/abs/2109.09960

June 17, 2022, 1:13 a.m. | Yicheng Wu, Zongyuan Ge, Donghao Zhang, Minfeng Xu, Lei Zhang, Yong Xia, Jianfei Cai

cs.CV updates on arXiv.org arxiv.org

In this paper, we propose a novel mutual consistency network (MC-Net+) to
effectively exploit the unlabeled data for semi-supervised medical image
segmentation. The MC-Net+ model is motivated by the observation that deep
models trained with limited annotations are prone to output highly uncertain
and easily mis-classified predictions in the ambiguous regions (e.g., adhesive
edges or thin branches) for medical image segmentation. Leveraging these
challenging samples can make the semi-supervised segmentation model training
more effective. Therefore, our proposed MC-Net+ model consists …

arxiv cv image learning medical segmentation semi-supervised

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