Web: http://arxiv.org/abs/2201.10675

Jan. 27, 2022, 2:10 a.m. | Xuxin Chen, Ximin Wang, Ke Zhang, Kar-Ming Fung, Theresa C. Thai, Kathleen Moore, Robert S. Mannel, Hong Liu, Bin Zheng, Yuchen Qiu

cs.CV updates on arXiv.org arxiv.org

This study aims to develop a novel computer-aided diagnosis (CAD) scheme for
mammographic breast mass classification using semi-supervised learning.
Although supervised deep learning has achieved huge success across various
medical image analysis tasks, its success relies on large amounts of
high-quality annotations, which can be challenging to acquire in practice. To
overcome this limitation, we propose employing a semi-supervised method, i.e.,
virtual adversarial training (VAT), to leverage and learn useful information
underlying in unlabeled data for better classification of breast …

arxiv classification cv training virtual

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