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Journal of Medical Systems
Published in: Journal of Medical Systems 5/2011

01-10-2011 | Original Paper

Highly Sensitive Computer Aided Diagnosis System for Breast Tumor Based on Color Doppler Flow Images

Authors: Xian-Fen Diao, Xin-Yu Zhang, Tian-Fu Wang, Si-Ping Chen, Ying Yang, Ling Zhong

Published in: Journal of Medical Systems | Issue 5/2011

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Abstract

A computer-aided diagnosis (CAD) system for breast tumor based on color Doppler flow images is proposed. Our system consists of automatic segmentation, feature extraction, and classification of breast tumors. First, the B-mode grayscale image containing anatomical information was separated from a color Doppler flow image (CDFI). Second, the boundary of the breast tumor was automatically defined in the B-mode image and then morphologic and gray features were extracted. Third, an optimal feature vector was created using K-means cluster algorithm. Then a back-propagation (BP) artificial neural network (ANN) was used to classify breast tumors as benign, malignant or uncertain. Finally, the blood flow feature was extracted selectively from the CDFI, and was used to classify the uncertain tumor as benign or malignant. Experiments on 500 cases show that the proposed system yields an accuracy of 100% for the malignant and 80.8% for the benign classification. Comparing with other systems, the advantage of our system is that it has a much lower percentage of malignant tumor misdiagnosis.
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Metadata
Title
Highly Sensitive Computer Aided Diagnosis System for Breast Tumor Based on Color Doppler Flow Images
Authors
Xian-Fen Diao
Xin-Yu Zhang
Tian-Fu Wang
Si-Ping Chen
Ying Yang
Ling Zhong
Publication date
01-10-2011
Publisher
Springer US
Published in
Journal of Medical Systems / Issue 5/2011
Print ISSN: 0148-5598
Electronic ISSN: 1573-689X
DOI
https://doi.org/10.1007/s10916-010-9461-8

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