Automatic breast ultrasound image segmentation: A survey. (July 2018)

• Record Type: Journal Article
• Authors: Xian, Min; Zhang, Yingtao; Cheng, H.D.; Xu, Fei; Zhang, Boyu; Ding, Jianrui
• Is Part Of: Pattern recognition. Volume 79(2018:Jul.)
• Page Start: 340
• Page End: 355
• Publication Date: 2018-07
• Subjects: Breast ultrasound (BUS) images -- Breast cancer -- Segmentation -- Benchmark -- Early detection -- Computer-aided diagnosis (CAD); Pattern perception -- Periodicals; Perception des structures -- Périodiques; Patroonherkenning; 006.4
• DOI: 10.1016/j.patcog.2018.02.012
• Languages: English
• ISSNs: 0031-3203

Abstract

Highlights: Summarize the four fundamental issues in BUS image segmentation. Study the basic ideas, theories, pros and cons of BUS image segmentation approaches, group them into categories, and extensively review each category in depth by discussing the principles, application issues, and advantages/disadvantages. Discuss the four major directions of BUS image segmentation. Abstract: Breast cancer is one of the leading causes of cancer death among women worldwide. In clinical routine, automatic breast ultrasound (BUS) image segmentation is very challenging and essential for cancer diagnosis and treatment planning. Many BUS segmentation approaches have been studied in the last two decades, and have been proved to be effective on private datasets. Currently, the advancement of BUS image segmentation seems to meet its bottleneck. The improvement of the performance is increasingly challenging, and only few new approaches were published in the last several years. It is the time to look at the field by reviewing previous approaches comprehensively and to investigate the future directions. In this paper, we study the basic ideas, theories, pros and cons of the approaches, group them into categories, and extensively review each category in depth by discussing the principles, application issues, and advantages/disadvantages.