A texture features based medical image retrieval system for breast cancer

Author

Jianlong Zhou ; Chang Feng ; Xiaoming Liu ; Tang, Ju

Author_Institution

Coll. of Comput. Sci. & Technol., Wuhan Univ. of Sci. & Technol., Wuhan, China

fYear

2012

fDate

3-5 Dec. 2012

Firstpage

1010

Lastpage

1015

Abstract

This paper designed and implemented a content-based medical image retrieval (CBMIR) system for mammograms images. The main functions of this system includes query module, feature extraction module, matching module and display module. The system uses the Euclidean distance as an image similarity measure, using the gray level co-occurrence matrix texture and Tamura texture feature extraction. Experiments are performed with 85 mass images from DDSM dataset, an average precision of 69% is achieved.

Keywords

cancer; content-based retrieval; feature extraction; image retrieval; image texture; mammography; matrix algebra; medical image processing; CBMIR system; DDSM dataset; Euclidean distance; Tamura texture feature extraction; breast cancer; content-based medical image retrieval system; display module; feature extraction module; gray level cooccurrence matrix texture; image similarity measure; mammogram images; matching module; query module; texture feature based medical image retrieval system; CBMIR; GLCM; Mammograms; Tamura;

fLanguage

English

Publisher

ieee

Conference_Titel

Computing and Convergence Technology (ICCCT), 2012 7th International Conference on

Conference_Location

Seoul

Print_ISBN

978-1-4673-0894-6

Type

conf

Filename

6530482