In-Vivo IVUS tissue classification: a comparison between RF signal analysis and reconstructed images

Authors:
Karla L. Caballero;Joel Barajas;Oriol Pujol;Neus Salvatella;Petia Radeva
Affiliations:
Computer Vision Center, UAB Bellaterra, Barcelona, Spain;Computer Vision Center, UAB Bellaterra, Barcelona, Spain;Computer Vision Center, UAB Bellaterra, Barcelona, Spain;Hospital Universitari German Trias i Pujol, Badalona, Spain;Computer Vision Center, UAB Bellaterra, Barcelona, Spain
Venue:
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Year:
2006

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Abstract

In this paper we present a novel framework for classification of the different kind of tissues in intravascular ultrasound (IVUS) data. We expose a normalized reconstruction of the IVUS images from radio frequency (RF) signals, and the use of these signals for classification. The reconstructed data is described in terms of texture based features and feeds an ECOC-Adaboost learning process. In the same manner, the RF signals are characterize using Autoregressive models, and classified with a similar learning process. A comparison is performed among these techniques and with DICOM based classification ones obtaining very promising results.