计算机科学 ›› 2020, Vol. 47 ›› Issue (11A): 145-150.doi: 10.11896/jsjkx.191100098
满芮1, 杨萍1, 季程雨1, 许博文2
MAN Rui1, YANG Ping1, JI Cheng-yu1, XU Bo-wen2
摘要: 乳腺癌组织病理学检查是乳腺癌诊断的“金标准”。乳腺癌组织病理学图像的分类已经成为医学图像处理领域的研究热点。图像的精确分类,在辅助医生诊断病情、满足临床应用需求等方面有着重大的应用价值。文中跟踪了乳腺癌组织病理学图像分类算法的研究进展,分析了相关算法的优缺点。按照是否需要手动提取图像特征,将乳腺癌组织病理学图像分类算法分为两大类,分别是传统的人工提取乳腺癌组织病理学图像特征的分类方法,以及基于深度学习算法的乳腺癌组织病理学图像分类方法。然后,对基于深度学习算法的乳腺癌组织病理学图像进行二分类或多分类的研究进行了进一步跟踪。最后,给出了应用深度学习最新理论的乳腺癌组织病理学图像分类算法,得出乳腺癌组织病理学图像分类研究的结论,并讨论了进一步的研究方向。
中图分类号:
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