%0 Conference Proceedings
%T Automatic Branching Detection in IVUS Sequences
%A Marina Alberti
%A Carlo Gatta
%A Simone Balocco
%A Francesco Ciompi
%A Oriol Pujol
%A Joana Silva
%A Xavier Carrillo
%A Petia Radeva
%E Jordi Vitria
%E Joao Miguel Raposo
%E Mario Hernandez
%B 5th Iberian Conference on Pattern Recognition and Image Analysis
%D 2011
%V 6669
%I Springer Berlin Heidelberg
%C Berlin
%@ 0302-9743
%@ 978-3-642-21256-7
%F Marina Alberti2011
%O MILAB;HuPBA
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1740), last updated on Thu, 06 Mar 2014 16:05:23 +0100
%X Atherosclerosis is a vascular pathology affecting the arterial walls, generally located in specific vessel sites, such as bifurcations. In this paper, for the first time, a fully automatic approach for the detection of bifurcations in IVUS pullback sequences is presented. The method identifies the frames and the angular sectors in which a bifurcation is visible. This goal is achieved by applying a classifier to a set of textural features extracted from each image of an IVUS pullback. A comparison between two state-of-the-art classifiers is performed, AdaBoost and Random Forest. A cross-validation scheme is applied in order to evaluate the performances of the approaches. The obtained results are encouraging, showing a sensitivity of 75% and an accuracy of 94% by using the AdaBoost algorithm.
%U http://dx.doi.org/10.1007/978-3-642-21257-4_16
%P 126-133