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Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

A. Taki, A. Roodaki, S.K. Setarehdan, P. Heider, N. Navab
Assessment of Automatic Classification of Artery Plaque Composition in IVUS Images Using Histology Correlation
22nd International Congress and Exhibition June 25 - 28, 2008, Barcelona, Spain (bib)

Intravascular ultrasound (IVUS) is becoming accepted as an imaging technique that allows precise tomographic assessment of the coronary anatomy in vivo in the latest 90’s. Clinical studies have documented the sensitivity of IVUS in detecting atherosclerosis and in quantifying the morphology of coronary lesions [2]. More importantly, IVUS can potentially quantify the structure and composition of normal and atherosclerotic coronary rather than relying on histological data which can only be obtained at autopsy. Mainly, there are two practical information that can be obtained by processing the IVUS data; one of them lead to detecting the Intima and Media-Adventitia borders, and the other help us to interpret the composition of arteries plaques. In this paper, we are focusing on characterizing the composition of atherosclerotic plaques via processing the IVUS images. A manual processing of images, apart from being a tedious time consuming task, might suffer from intra- and interobserver variability. Besides, it is not possible for an expert to completely characterize the different composition of atherosclerotic plaques. Therefore, automatic characterization of IVUS images becomes a necessity. The effect of several texture analysis features have been investigated for this purpose in the literature [3, 4]. The limitation of these papers is that the result of their method was compared with the characterized image by expert. On the other hand, in some papers methods based on processing of IVUS signal have been proposed in order to recognizing different substances in atherosclerotic plaques.
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