论文标题
基于深度学习的乳腺癌成像的计算机辅助系统：一项关键评论
Deep Learning Based Computer-Aided Systems for Breast Cancer Imaging : A Critical Review
论文作者
论文摘要
本文使用超声和乳房X线摄影图像对乳腺肿瘤诊断中深度学习应用的文献进行了批判性综述。它还总结了计算机辅助诊断（CAD）系统的最新进展，这些系统利用新的深度学习方法自动识别图像并提高放射科医生做出的诊断的准确性。这篇评论基于过去十年（2010年1月2020年1月）在过去十年中发表的文献。分类过程中的主要发现表明，新的DL-CAD方法是用于乳腺癌的有用且有效的筛查工具，从而减少了手动特征提取的需求。乳腺肿瘤研究界可以利用这项调查作为其当前和未来研究的基础。
This paper provides a critical review of the literature on deep learning applications in breast tumor diagnosis using ultrasound and mammography images. It also summarizes recent advances in computer-aided diagnosis (CAD) systems, which make use of new deep learning methods to automatically recognize images and improve the accuracy of diagnosis made by radiologists. This review is based upon published literature in the past decade (January 2010 January 2020). The main findings in the classification process reveal that new DL-CAD methods are useful and effective screening tools for breast cancer, thus reducing the need for manual feature extraction. The breast tumor research community can utilize this survey as a basis for their current and future studies.
