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  • 标题:Real-Time Evaluation of Breast Self-Examination Using Computer Vision
  • 本地全文:下载
  • 作者:Eman Mohammadi ; Elmer P. Dadios ; Laurence A. Gan Lim
  • 期刊名称:International Journal of Biomedical Imaging
  • 印刷版ISSN:1687-4188
  • 电子版ISSN:1687-4196
  • 出版年度:2014
  • 卷号:2014
  • DOI:10.1155/2014/924759
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Breast cancer is the most common cancer among women worldwide and breast self-examination (BSE) is considered as the most cost-effective approach for early breast cancer detection. The general objective of this paper is to design and develop a computer vision algorithm to evaluate the BSE performance in real-time. The first stage of the algorithm presents a method for detecting and tracking the nipples in frames while a woman performs BSE; the second stage presents a method for localizing the breast region and blocks of pixels related to palpation of the breast, and the third stage focuses on detecting the palpated blocks in the breast region. The palpated blocks are highlighted at the time of BSE performance. In a correct BSE performance, all blocks must be palpated, checked, and highlighted, respectively. If any abnormality, such as masses, is detected, then this must be reported to a doctor to confirm the presence of this abnormality and proceed to perform other confirmatory tests. The experimental results have shown that the BSE evaluation algorithm presented in this paper provides robust performance.
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