NDLI: Classification of benign and malignant breast tumors by the contour analysis and scatterers characterization

Content Provider	IEEE Xplore Digital Library
Author	Yin-Yin Liao Chih-Kuang Yeh Po-Hsiang Tsui Chien-Cheng Chang
Copyright Year	2009
Description	Author affiliation: Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan (Yin-Yin Liao; Chih-Kuang Yeh) \|\| Division of Mechanics, Research Center for Applied Sciences, Academia Sinica, Taipei, Taiwan (Po-Hsiang Tsui; Chien-Cheng Chang)
Abstract	The B-scan reflects the intensity of the reflected echoes, and is clever at a clear description of tumor contour to provide knowledge of morphology, and the Nakagami image reflects the statistical distribution of local backscattered signals, which is associated with the arrangements and concentrations of scatterers in tumors. In this study, we explored the clinical performance of combining the B-scan-based tumor contour analysis and the Nakagami-image-based tumor scatterers characterization in classifying benign and malignant breast tumors. To confirm this concept, rawdata obtained from 60 clinical cases were acquired. The B-mode images were used to calculate the standard deviation of the shortest path for contour feature analysis, and the Nakagami images were applied to estimate the average Nakagami parameters in the region of interests (ROI) in tumors. Overall, malignant tumors were highly irregular in tumor contour, whereas they had lower average Nakagami parameters in scatterers characterization. The receiver operating characteristic (ROC) curve and fuzzy c-means (FCM) clustering were used to estimate the performances of combining two parameters in classifying tumors. The clinical results showed that there would be a tradeoff between the sensitivity and specificity when using a single parameter to differentiate benign and malignant tumors. The ROC analysis demonstrated that the standard deviation (SD) of the shortest distance had a diagnostic accuracy of 81.7%, sensitivity of 76.7%, and specificity of 86.7%. The Nakagami parameter had a diagnostic accuracy of 80%, sensitivity of 86.7%, and specificity of 73.3%. However, the combination of the SD of the shortest distance and the Nakagami parameter concurrently allows both the sensitivity and specificity to exceed 80%, making the performance to diagnose breast tumors better.
Starting Page	2488
Ending Page	2491
File Size	1646732
Page Count	4
File Format	PDF
ISBN	9781424443895
ISSN	19485727
DOI	10.1109/ULTSYM.2009.5441446
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-20
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cancer Breast tumors Scattering Breast neoplasms Malignant tumors Sensitivity and specificity Morphology Nakagami distribution Statistical distributions Performance analysis scatterers characterization Breast tumor classification Nakagami image Contour
Content Type	Text
Resource Type	Article

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