计算机科学 ›› 2022, Vol. 49 ›› Issue (11A): 210800232-9.doi: 10.11896/jsjkx.210800232
张喜科, 马志庆, 赵文华, 崔冬梅
ZHANG Xi-ke, MA Zhi-qing, ZHAO Wen-hua, CUI Dong-mei
摘要: 乳腺癌组织病理学检查是确诊乳腺癌的“金标准”。基于卷积神经网络的乳腺癌组织病理学图像分类已经成为医学图像处理与分析领域的研究热点之一。自动且精确的乳腺癌组织病理学图像分类在临床上具有重要的应用价值。首先介绍了两个目前广泛应用于乳腺癌组织病理学图像分类的公开数据集及各自的评价标准。然后,重点阐述了卷积神经网络在两个数据集上的研究进展。在描述研究进展的过程中,分析了部分模型准确率较低的原因,并对提升模型性能给出了一些建议。最后,讨论了乳腺癌组织病理学图像分类目前存在的问题及对未来的展望。
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