Region of interest identification in prostate TRUS images based on Gabor filter

Author

Mohamed, S.S. ; El-Saadany, E.F. ; Abdel-Galil, T.K. ; Shen, J. ; Salama, M.M.A. ; Fenster, A. ; Downey, D.B. ; Rizkalla, K.

Author_Institution

Waterloo Univ., Ont.

Volume

1

fYear

2003

fDate

30-30 Dec. 2003

Firstpage

415

Abstract

This paper presents a new algorithm for prostate texture classification based on transrectal ultrasound (TRUS) images. A Gabor filter is designed to automatically identify the regions of interest (ROI) in the image. Furthermore, texture analysis for these regions is carried out by employing grey level co-occurrence matrix GLCM. Contrast feature is found to be useful for the differentiation between cancerous and non-cancerous tissues. The obtained results demonstrate that the contrast level in normal tissue is higher than that of cancerous tissue

Keywords

Gabor filters; biological tissues; biomedical ultrasonics; cancer; image classification; image texture; medical image processing; ultrasonic imaging; Gabor filter; cancerous tissue; grey level co-occurrence matrix; noncancerous tissue; prostate TRUS images; prostate texture classification; prostrate cancer; texture analysis; transrectal ultrasound images; Feature extraction; Frequency; Gabor filters; Glands; Image analysis; Image resolution; Image segmentation; Image texture analysis; Prostate cancer; Ultrasonic imaging; Gabor filter and Grey level co-occurrence matrix; Prostrate cancer;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2003 IEEE 46th Midwest Symposium on

Conference_Location

Cairo

ISSN

1548-3746

Print_ISBN

0-7803-8294-3

Type

conf

DOI

10.1109/MWSCAS.2003.1562307

Filename

1562307