gms | German Medical Science

33. Internationale Konferenz für Elektrokardiographie

Internationale Konferenz für Elektrokardiographie

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

Die elektronische Version dieses Artikels ist vollständig und ist verfügbar unter: http://www.egms.de/de/meetings/ice2006/06ice031.shtml

Veröffentlicht: 8. Februar 2007

© 2007 Margret.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.de). Er darf vervielf&aauml;ltigt, verbreitet und &oauml;ffentlich zug&aauml;nglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.


Gliederung

Text

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.