GRETSI'03 -- Proceedings

	19^st GRETSI Symposium on Signal and Image Processing Paris 8 - 11 september 2003

Information related to the paper

Title

Classification of hepatic metastasis in enhanced CT images by dipolar decision tree

Author(s)

Marek Kretowski	Bialystok Technical University
Johanne Bezy-Wendling	INSERM, Universite de Rennes 1
Dorota Duda	Bialystok Technical University

Rererences

vol. III, page 327

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Abstract

In the paper, computer-aided decision support system for hepatic metastasis diagnosis based on dynamic CT scans is presented. Analyzed image database contains 4 types of pathological lesions and normal tissue in typical acquisition time moments of dynamic CT of the liver: without contrast material and after injection, in arterial and portal phases. In the proposed approach, texture analysis of drawn ROI-s is combined with a new classification method - dipolar decision tree. In this method, each node of the binary tree corresponds to a multivariate test (hyper-plane). Searching for an optimal position of the hyper-plane is based on separation of mixed dipoles (pairs of input feature vectors from different classes). Experimental results show that the proposed approach allowed obtaining the competitive classification quality. Furthermore, it could be improved by taking into account the acquisition time of CT images.

Edition : Télécom-Paris -- 2003