Segmentation of ultrasound images by using wavelet transform

Author

Kurnaz, M.N. ; Dokur, Z. ; Ölmez, T.

Author_Institution

Dept. of Electron. & Commun. Eng., Istanbul Tech. Univ., Turkey

Volume

1

fYear

2003

fDate

17-21 Sept. 2003

Firstpage

657

Abstract

This paper presents a new feature extraction method for the segmentation of ultrasound images. Wavelet transform is proposed for determination of the textures in the ultrasound images. Elements of the feature vectors are formed by the wavelet coefficients at several decomposition level. In this study, incremental self-organized neural network (INeN) is proposed as the classifier. The classification performance is increased by using the wavelet transform and the INeN together.

Keywords

biomedical ultrasonics; feature extraction; image classification; image segmentation; image texture; medical image processing; self-organising feature maps; wavelet transforms; INeN; classification performance; feature extraction; image textures; incremental self-organized neural network; segmentation; ultrasound images; wavelet transform; Artificial neural networks; Biomedical imaging; Data mining; Filters; Frequency; Image segmentation; Network topology; Neural networks; Ultrasonic imaging; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE

ISSN

1094-687X

Print_ISBN

0-7803-7789-3

Type

conf

DOI

10.1109/IEMBS.2003.1279845

Filename

1279845