Classification of Breast Masses Based on Multi-View Information Fusion Using Multi-Agent Method

Author

Zhao, Huanping ; Xu, Weidong ; Li, Lihua ; Zhang, Juan

Author_Institution

Inst. for Biomed. Eng. & Instrum., Hangzhou Dianzi Univ., Hangzhou, China

fYear

2011

fDate

10-12 May 2011

Firstpage

1

Lastpage

4

Abstract

Mammography is an important detection method of breast cancer, and classification of mammographic masses plays an important role in Computer-aided diagnosis (CAD) for breast cancer. In this paper, one novel multi-view information fusion algorithm based on Multi-Agent (MA) method is proposed to improve the accuracy of classification of masses. 128 ROIs (regions of interest) from DDSM database composed by 64 pairs of cranio-caudal (CC) view and medio-lateral oblique (MLO) view were chosen for the experiments, which demonstrated the proposed algorithm improved the accuracy and reduced the false positive rates rather than the other methods.

Keywords

cancer; diagnostic radiography; image classification; image fusion; mammography; medical image processing; CAD; DDSM database; breast cancer detection method; breast mass classification; computer aided diagnosis; cranio-caudal view; mammography; mass classification accuracy; mediolateral oblique view; multiagent method; multiview information fusion algorithm; Accuracy; Breast cancer; Classification algorithms; Design automation; Solid modeling;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International Conference on

Conference_Location

Wuhan

ISSN

2151-7614

Print_ISBN

978-1-4244-5088-6

Type

conf

DOI

10.1109/icbbe.2011.5780304

Filename

5780304