ECOC Random Fields for Lumen Segmentation in Radial Artery IVUS Sequences

Authors:
Francesco Ciompi;Oriol Pujol;Eduard Fernández-Nofrerías;Josepa Mauri;Petia Radeva
Affiliations:
Dep. of Applied Mathematics and Analysis, University of Barcelona, Spain and Computer Vision Center, Bellaterra, Spain;Dep. of Applied Mathematics and Analysis, University of Barcelona, Spain and Computer Vision Center, Bellaterra, Spain;University Hospital "Germans Trias i Pujol", Badalona, Spain;University Hospital "Germans Trias i Pujol", Badalona, Spain;Dep. of Applied Mathematics and Analysis, University of Barcelona, Spain and Computer Vision Center, Bellaterra, Spain
Venue:
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Year:
2009

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Abstract

The measure of lumen volume on radial arteries can be used to evaluate the vessel response to different vasodilators. In this paper, we present a framework for automatic lumen segmentation in longitudinal cut images of radial artery from Intravascular ultrasound sequences. The segmentation is tackled as a classification problem where the contextual information is exploited by means of Conditional Random Fields (CRFs). A multi-class classification framework is proposed, and inference is achieved by combining binary CRFs according to the Error-Correcting-Output-Code technique. The results are validated against manually segmented sequences. Finally, the method is compared with other state-of-the-art classifiers.