Hierarchical Prototype Alignment And Regularization For Semi-Supervised Alopecia Areata Segmentation

    Enting Gao, Xinghua Dong, Yonggang Li, Junhui Zhu, X Chen, Naihui Zhou, Dehui Xiang
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    Studysummary This study introduced a novel framework that significantly improves the accuracy of alopecia areata lesion segmentation in semi-supervised scenarios, outperforming existing methods and aiding in the disease's diagnosis, treatment, and staging, which can impact quality of life and mental well-being.
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