Orthogonal Moments Based Texture Analysis of CT Liver Images

Author

Bharathi, V. Subbiah ; Vijilious, M. A Leo ; Ganesan, L.

Author_Institution

DMI Coll. of Eng., Chennai

Volume

2

fYear

2007

fDate

13-15 Dec. 2007

Firstpage

249

Lastpage

253

Abstract

Orthogonal moments such as Zernike moments and Legendre moments have been proven to have superior feature representation capability and low information redundancy. The number of orthogonal moments to be used as features or numerical attributes to perform any application is minimal due to the orthogonal nature. However, the information possessed by each moment order needs to be analysed to identify the appropriate moment orders for the undertaken task. In this work, a statistical significance test has been performed to select the best moment orders to discriminate normal and abnormal tissues in liver images. The experimental results reveal the efficacy of the proposed features.

Keywords

biological tissues; computerised tomography; image texture; liver; medical image processing; statistical testing; CT liver images; Legendre moments; Zernike moments; abnormal tissues; feature representation capability; information redundancy; orthogonal moments; statistical significance test; texture analysis; Computed tomography; Educational institutions; Fractals; Image analysis; Image edge detection; Image texture analysis; Lesions; Liver neoplasms; Magnetic resonance imaging; Neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Conference on Computational Intelligence and Multimedia Applications, 2007. International Conference on

Conference_Location

Sivakasi, Tamil Nadu

Print_ISBN

0-7695-3050-8

Type

conf

DOI

10.1109/ICCIMA.2007.187

Filename

4426702