Breast cancer is one of the most common malignancies. Pathological image processing of breast has become an important means for early diagnosis of breast cancer. Using medical image processing to assist doctors to detect potential breast cancer as early as possible has always been a hot topic in the field of medical image diagnosis. In this paper, a breast cancer recognition method based on image processing is systematically expounded from four aspects: breast cancer detection, image segmentation, image registration, and image fusion. The achievements and application scope of supervised learning, unsupervised learning, deep learning, CNN, and so on in breast cancer examination are expounded. The prospect of unsupervised learning and transfer learning for breast cancer diagnosis is prospected. Finally, the privacy protection of breast cancer patients is put forward.

中文翻译：

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乳腺癌病理图像处理综述


乳腺癌是最常见的恶性肿瘤之一。乳腺病理图像处理已成为乳腺癌早期诊断的重要手段。利用医学图像处理协助医生尽早发现潜在的乳腺癌一直是医学图像诊断领域的热门话题。本文从乳腺癌检测、图像分割、图像配准、图像融合四个方面系统阐述了一种基于图像处理的乳腺癌识别方法。阐述了监督学习、无监督学习、深度学习、CNN等在乳腺癌检查中的成果和应用范围。展望了无监督学习和迁移学习在乳腺癌诊断中的应用前景。最后提出乳腺癌患者的隐私保护。