Computer-Aided Detection Based on Fuzzy Support Vector Machines

Author

Bai Xingli ; Xu, Qian

Author_Institution

Sch. of Mech. Electron. & Inf. Eng., China Univ. of Min. & Technol., Beijing

Volume

1

fYear

2008

fDate

17-18 Oct. 2008

Firstpage

202

Lastpage

206

Abstract

The paper present a novel method for Medical image Detection using fuzzy support vector machines. Through calculating fuzzy membership of every sample, the conception of fuzzy support vector machine (FSVM) is introduced, which can resolve the problem of unclassifiable regions in SVM. Some experiments for Microcalcifications detection in digital mammography with different noise levels were conducted and results show that the proposed method is able to detection the breast cancer in the images of mammography with high precision.

Keywords

cancer; feature extraction; fuzzy set theory; image classification; mammography; medical image processing; support vector machines; breast cancer; computer-aided medical image detection; digital mammography; feature extraction; fuzzy membership; fuzzy support vector machine; unclassifiable region; Biomedical engineering; Biomedical imaging; Breast cancer; Cancer detection; Design engineering; Fuzzy sets; Mammography; Medical diagnostic imaging; Support vector machine classification; Support vector machines; Breast Cancer; Fuzzy Support Vector Machines; Mammography; Membership Degree;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Design, 2008. ISCID '08. International Symposium on

Conference_Location

Wuhan

Print_ISBN

978-0-7695-3311-7

Type

conf

DOI

10.1109/ISCID.2008.209

Filename

4725591