Detection and classification of masses in breast ultrasound images

被引:76
|
作者
Shi, Xiangjun [1 ]
Cheng, H. D. [1 ]
Hu, Liming [1 ]
Ju, Wen [1 ]
Tian, Jiawei [2 ]
机构
[1] Utah State Univ, Dept Comp Sci, Logan, UT 84322 USA
[2] Harbin Med Coll, Dept Ultrasound, Affiliated Hosp 2, Harbin 150001, Peoples R China
关键词
Breast cancer; Breast sonography; Computer-aided diagnosis (CAD); Feature selection; Fuzzy support vector machine (FSVM); Mass classification; Ultrasound (US) images; SUPPORT VECTOR MACHINES; TEXTURE ANALYSIS; DIAGNOSIS; LESIONS; SONOGRAPHY; CANCER; BENIGN;
D O I
10.1016/j.dsp.2009.10.010
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Breast cancer can be treated most effectively when detected in its early stage. Due to the superiority to mammography in its ability to detect focal abnormalities in the dense breasts of adolescent women, sonography has become an important adjunct to mammography in breast cancer detection and has been especially useful in distinguishing cysts from solid tumors. In this paper, we develop a novel CAD system based on fuzzy support vector machine to automatically detect and classify mass using ultrasound (US) images. The experimental results show that the proposed system greatly improves the five objective measurements and the area (A(z)) under the ROC curve compared with those of other classification methods, and radiologist assessments, and the proposed approach will be very valuable for breast cancer control. (C) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:824 / 836
页数:13
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