Feb. 8, 2024, 5:47 a.m. | Ye Zhang Ziyue Wang Yifeng Wang Hao Bian Linghan Cai Hengrui Li Lingbo Zhang Yongbing Zhang

cs.CV updates on arXiv.org arxiv.org

Semi-supervised segmentation methods have demonstrated promising results in natural scenarios, providing a solution to reduce dependency on manual annotation. However, these methods face significant challenges when directly applied to pathological images due to the subtle color differences between nuclei and tissues, as well as the significant morphological variations among nuclei. Consequently, the generated pseudo-labels often contain much noise, especially at the nuclei boundaries. To address the above problem, this paper proposes a boundary-aware contrastive learning network to denoise the boundary …

annotation challenges color cs.cv differences face images instance natural reduce segmentation semi-supervised solution

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