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基于深度学习的乳腺 X 线摄影人工智能。

Deep Learning-Based Artificial Intelligence for Mammography.

机构信息

Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Seoul, Korea.

Department of Radiology, Yongin Severance Hospital, Yonsei University, College of Medicine, Yongin, Korea.

出版信息

Korean J Radiol. 2021 Aug;22(8):1225-1239. doi: 10.3348/kjr.2020.1210. Epub 2021 May 4.

Abstract

During the past decade, researchers have investigated the use of computer-aided mammography interpretation. With the application of deep learning technology, artificial intelligence (AI)-based algorithms for mammography have shown promising results in the quantitative assessment of parenchymal density, detection and diagnosis of breast cancer, and prediction of breast cancer risk, enabling more precise patient management. AI-based algorithms may also enhance the efficiency of the interpretation workflow by reducing both the workload and interpretation time. However, more in-depth investigation is required to conclusively prove the effectiveness of AI-based algorithms. This review article discusses how AI algorithms can be applied to mammography interpretation as well as the current challenges in its implementation in real-world practice.

摘要

在过去的十年中,研究人员已经研究了计算机辅助乳房 X 线摄影解释的应用。随着深度学习技术的应用,基于人工智能(AI)的乳房 X 线摄影算法在乳腺实质密度的定量评估、乳腺癌的检测和诊断以及乳腺癌风险的预测方面显示出了有前途的结果,使患者的管理更加精确。基于 AI 的算法还可以通过减少工作量和解释时间来提高解释工作流程的效率。然而,还需要更深入的研究来最终证明基于 AI 的算法的有效性。本文综述了 AI 算法如何应用于乳房 X 线摄影解释,以及在实际应用中实施该算法所面临的挑战。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cbc/8316774/92c7f80e481e/kjr-22-1225-g001.jpg

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