%0 Conference Proceedings
%T ECOC Random Fields for Lumen Segmentation in Radial Artery IVUS Sequences
%A Francesco Ciompi
%A Oriol Pujol
%A E Fernandez-Nofrerias
%A J. Mauri
%A Petia Radeva
%B 12th International Conference on Medical Image and Computer Assisted Intervention
%D 2009
%V 5762
%N II
%I Springer Berlin Heidelberg
%@ 0302-9743
%@ 978-3-642-04270-6
%F Francesco Ciompi2009
%O MILAB;HuPBA
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1228), last updated on Tue, 17 Dec 2013 15:20:05 +0100
%X 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.
%U http://dx.doi.org/10.1007/978-3-642-04271-3_105