Tissues image retrieval system based on co-occuerrence, run length and roughness features

Author

George, L.E. ; Mohammed, E.Z.

Author_Institution

Dept. of Comput. Sci., Univ. of Baghdad, Baghdad, Iraq

fYear

2013

fDate

20-22 Jan. 2013

Firstpage

1

Lastpage

6

Abstract

The research presented in this paper was aimed to improve the retrieval performance of an images retrieval system in medical applications based on texture features. In general, the work consists of two phases: (1) enrollment phase, which consist of feature extraction based on Co-occurrence matrix and run length matrix features combined with developed method to measure the roughness, (2) retrieving phase, which use the artificial neural network and similarity measurement. The conducted tests were carried on 600 medical images from four types of tissues (i.e., blood cells, breast tissues, GI tissues, liver tissues) and give very high precision and recall rates (100,98).

Keywords

biological tissues; feature extraction; image retrieval; image texture; matrix algebra; medical image processing; neural nets; GI tissue; artificial neural network; blood cell; breast tissue; cooccuerrence feature; cooccurrence matrix; enrollment phase; feature extraction; liver tissue; medical application; precision rate; recall rate; retrieval performance; retrieving phase; roughness feature; run length feature; run length matrix; similarity measurement; texture feature; tissue image retrieval system; Artificial neural networks; Databases; Feature extraction; Medical diagnostic imaging; Training; Vectors; Coccurrence matrix; image retrieval; medical diagnosis; neural network; run length matrix; texture analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Medical Applications (ICCMA), 2013 International Conference on

Conference_Location

Sousse

Print_ISBN

978-1-4673-5213-0

Type

conf

DOI

10.1109/ICCMA.2013.6506186

Filename

6506186