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《工程(英文)》 >> 2019年 第5卷 第2期 doi: 10.1016/j.eng.2018.11.020

深度学习在医学超声图像分析中的应用综述

a National-Regional Key Technology Engineering Laboratory for Medical Ultrasound & Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging & School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, China
b Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China

收稿日期: 2018-03-01 修回日期: 2018-07-18 录用日期: 2018-11-08 发布日期: 2019-01-29

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摘要

在临床上,超声(US)已成为最主要的成像模态之一。超声是一种快速发展的技术,具有无痛苦、无电离辐射、经济适用、实时成像等优点;同时也有成像质量差、差异性大等特有的缺点。对于图像分析来说,很有必要开发先进的自动化超声图像分析方法来帮助医生进行超声诊断,一方面可以减轻医生的负担,另一方面可以降低诊断的主观性,从而使得诊断更加客观与准确。近年来,深度学习已经成为最主要的机器学习工具,并且广泛应用于各个研究领域,尤其是一般的图像分析与计算机视觉。在医学超声图像分析中,深度学习也展示了巨大的应用潜力。本文首先简要介绍了一些流行的深度学习结构,然后总结并全面讨论了深度学习方法在超声图像分析的各种特定任务(如图像分类、物体检测与目标分割)中的应用。最后,本文讨论了深度学习在医学超声图像分析应用中所面临的挑战以及潜在的发展趋势。

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