Real-Time Evaluation of Breast Self-Examination Using Computer Vision
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 performanc...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2014/924759 |
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| _version_ | 1832556131460841472 |
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| author | Eman Mohammadi Elmer P. Dadios Laurence A. Gan Lim Melvin K. Cabatuan Raouf N. G. Naguib Jose Maria C. Avila Andreas Oikonomou |
| author_facet | Eman Mohammadi Elmer P. Dadios Laurence A. Gan Lim Melvin K. Cabatuan Raouf N. G. Naguib Jose Maria C. Avila Andreas Oikonomou |
| author_sort | Eman Mohammadi |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-044a5c5d59b54189a463494929775d2d |
| institution | Kabale University |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-044a5c5d59b54189a463494929775d2d2025-02-03T05:46:13ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962014-01-01201410.1155/2014/924759924759Real-Time Evaluation of Breast Self-Examination Using Computer VisionEman Mohammadi0Elmer P. Dadios1Laurence A. Gan Lim2Melvin K. Cabatuan3Raouf N. G. Naguib4Jose Maria C. Avila5Andreas Oikonomou6De La Salle University, 2401 Taft Avenue, Malate, Manila, 1004 Metro Manila, PhilippinesDe La Salle University, 2401 Taft Avenue, Malate, Manila, 1004 Metro Manila, PhilippinesDe La Salle University, 2401 Taft Avenue, Malate, Manila, 1004 Metro Manila, PhilippinesDe La Salle University, 2401 Taft Avenue, Malate, Manila, 1004 Metro Manila, PhilippinesBIOCORE Research and Consultancy International, Liverpool, UKThe University of the Philippines, PhilippinesNottingham Trent University, UKBreast 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.http://dx.doi.org/10.1155/2014/924759 |
| spellingShingle | Eman Mohammadi Elmer P. Dadios Laurence A. Gan Lim Melvin K. Cabatuan Raouf N. G. Naguib Jose Maria C. Avila Andreas Oikonomou Real-Time Evaluation of Breast Self-Examination Using Computer Vision International Journal of Biomedical Imaging |
| title | Real-Time Evaluation of Breast Self-Examination Using Computer Vision |
| title_full | Real-Time Evaluation of Breast Self-Examination Using Computer Vision |
| title_fullStr | Real-Time Evaluation of Breast Self-Examination Using Computer Vision |
| title_full_unstemmed | Real-Time Evaluation of Breast Self-Examination Using Computer Vision |
| title_short | Real-Time Evaluation of Breast Self-Examination Using Computer Vision |
| title_sort | real time evaluation of breast self examination using computer vision |
| url | http://dx.doi.org/10.1155/2014/924759 |
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