首页 | 本学科首页   官方微博 | 高级检索  
     

基于乳腺X线摄影的肿块检测综述
引用本文:王俊茜,徐勇,孙利雷,蒲祖辉.基于乳腺X线摄影的肿块检测综述[J].自动化学报,2021,47(4):747-764.
作者姓名:王俊茜  徐勇  孙利雷  蒲祖辉
作者单位:1.哈尔滨工业大学(深圳) 计算机科学与技术学院 生物计算研究中心 深圳 518055
基金项目:深圳市科技创新委员会GJHZ20180419190732022贵州省公共大数据重点实验室开放课题基金2018BDKFJJ001
摘    要:早期筛查和及时治疗是控制乳腺癌死亡率最为有效的方法.乳腺X线摄影检查作为医学界公认的最有效的早期乳腺癌筛检工具, 可以很好地反映出乳腺存在的异常情况.在临床应用中, 乳腺癌的X线摄影直接征象为钙化和肿块, 对乳腺X线摄影中钙化点的检测技术已经相当的成熟, 但对肿块区域的检测和分类依旧是一项具有挑战性的任务. 因此, 本文对近几年提出的基于全乳腺X线摄影的肿块检测方法进行简要综述, 分别从基于传统的乳腺肿块检测与分割方法和基于深度学习的乳腺肿块检测方法进行介绍, 并讨论了乳腺X线摄影中肿块检测未来研究的发展趋势.

关 键 词:乳腺X线摄影    乳腺肿块检测    计算机辅助检测和诊断    深度学习
收稿时间:2018-10-12

Survey of Mass Detection Based on Mammography
Affiliation:1.Bio-Computing Research Center, College of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Shenzhen 5180552.Peng Cheng Laboratory, Shenzhe 5180003.College of Computer Science and Technology, Guizhou University, Guiyang 5500254.Guizhou Provincial Key Laboratory of Public Big Data, Guizhou University, Guiyang 5500255.Shenzhen Second People's Hospital (The First Affiliated Hospital of Shenzhen University), Shenzhen 518035
Abstract:Early screening and timely treatment are the most effective ways to control the mortality of breast cancer. Mammography is recognized as the most effective early breast cancer screening tool in the medical field nowadays, and it can well reflect abnormalities in the breast. In clinical application, the direct signs of breast cancer in mammography are calcification and mass. The detection technique of calcification in mammography is quite mature, but the detection and classification of the breast mass is still a challenging task. Therefore, this paper briefly reviews the methods of mass detection based on full mammography in recent years. We introduce the mass detection methods based on traditional mass detection and segmentation methods and deep learning mass detection methods, respectively. Finally, we summarize the proposed mass detection methods, and we also discuss the development trend of future research on mass detection in mammography.
Keywords:
点击此处可从《自动化学报》浏览原始摘要信息
点击此处可从《自动化学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号