gms | German Medical Science

33rd International Congress on Electrocardiology

International Society of Electrocardiology

A Novel Segmentation of Ultrasound Medical Images

Meeting Abstract

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  • corresponding author presenting/speaker A. Margret - Coimbatore, Karunya, Indien

33rd International Congress on Electrocardiology. Cologne, 28.06.-01.07.2006. Düsseldorf, Köln: German Medical Science; 2007. Doc06ice031

The electronic version of this article is the complete one and can be found online at:

Published: February 8, 2007

© 2007 Margret.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.



This paper presents a novel texture and shape priors based method for segmentation in ultrasound medical images. Texture features are extracted by applying a bank of Gabor filters on images through a two-sided convolution strategy. The texture model is constructed via estimating the parameters of a set of mixtures of half-planed Gaussians using the expectation-maximization method. Through this texture model, the texture similarities of areas around the segmenting curve are measured in the inside and outside regions, respectively. We also present an iterative segmentation framework to combine the texture measures into the parametric Shape Model. The goal of this energy function is to partition the test image into two regions, the inside one with high texture similarity and low texture variance, and the outside one with high texture variance. The effectiveness of this method is demonstrated through experimental results on both natural images and ultrasound data compared with other image segmentation methods.