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Automated Analysis of Ultrasound Videos for Detection of Breast Lesions | ||
| Middle East Journal of Cancer | ||
| مقاله 9، دوره 11، شماره 1 - شماره پیاپی 41، فروردین 2020، صفحه 80-90 اصل مقاله (2.71 M) | ||
| نوع مقاله: Original Article(s) | ||
| شناسه دیجیتال (DOI): 10.30476/mejc.2019.78692.0 | ||
| نویسندگان | ||
| Mohammad Mehdi Movahedi1، 2؛ Ali Zamani1؛ Hossein Parsaei* 1، 3؛ Ali Tavakoli Golpaygani4؛ Mohammad Reza Haghighi Poya1 | ||
| 1Department of Medical Physics and Engineering, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran | ||
| 2Ionizing and Non-ionizing Radiation Protection Research Center (INIRPRC), Shiraz University of Medical Sciences, Shiraz, Iran | ||
| 3Shiraz Neuroscience Research Center, Shiraz University of Medical Sciences, Shiraz, Iran | ||
| 4Department of Biomedical Engineering, Standard Research Institute, Karaj, Iran | ||
| چکیده | ||
| Background: Breast cancer is the second cause of death among women. Ultrasound (US) imaging is the most common technique for diagnosing breast cancer; however, detecting breast lesions in US images is a difficult task, mainly, because it provides low-quality images. Consequently, identifying lesions in US images is still a challenging task and an open problem in US image processing. This study aims to develop an automated system for the identification of lesions in US images Method: We proposed an automatic method to assist radiologists in inspecting and analyzing US images in breast screening and diagnosing breast cancer. In contrast to previous research, this work focuses on fusing information extracted from different frames. The developed method consists of template matching, morphological features extraction, local binary patterns, fuzzy C-means clustering, region growing, and information fusion-based image segmentation technique. The performance of the system was evaluated using a database composed of 22 US videos where 10 breast US films were obtained from patients with breast lesions and 12 videos belonged to normal cases. Results: The sensitivity, specificity, and accuracy of the system in detecting frames with breast lesions were 95.7%, 97.1%, and 97.1%, respectively. The algorithm reduced the vibration of the physician’s hands’ while probing by assessing every 10 frames regardless of the results of the prior frame; hence, lowering the possibility of missing a lesion during an examination. Conclusion: The presented system outperforms several existing methods in correctly detecting breast lesions in a breast cancer screening test. Fusing information that exists in frames of a breast US film can help improve the identification of lesions (suspect regions) in a screening test. | ||
| کلیدواژه‌ها | ||
| Automatic lesion detection؛ Breast lesion؛ Ultrasound imaging segmentation؛ Ultrasound video analysis | ||
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آمار تعداد مشاهده مقاله: 3,749 تعداد دریافت فایل اصل مقاله: 2,052 |
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