%0 Conference Proceedings
%T Accurate and Robust Fully-Automatic QCA: Method and Numerical  Validation
%A Antonio Hernandez
%A Carlo Gatta
%A Sergio Escalera
%A Laura Igual
%A Victoria Martin Yuste
%A Petia Radeva
%B 14th International Conference on Medical Image Computing and Computer Assisted Intervention
%D 2011
%V 14
%N 3
%I Springer
%@ 978-3-642-23625-9
%F Antonio Hernandez2011
%O MILAB;HuPBA
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1769), last updated on Fri, 07 Mar 2014 10:49:51 +0100
%X The Quantitative Coronary Angiography (QCA) is a methodology used to evaluate the arterial diseases and, in particular, the degree of stenosis. In this paper we propose AQCA, a fully automatic method for vessel segmentation based on graph cut theory. Vesselness, geodesic paths and a new multi-scale edgeness map are used to compute a globally optimal artery segmentation. We evaluate the method performance in a rigorous numerical way on two datasets. The method can detect an artery with precision 92.9 +/- 5% and sensitivity 94.2 +/- 6%. The average absolute distance error between detected and ground truth centerline is 1.13 +/- 0.11 pixels (about 0.27 +/- 0.025 mm) and the absolute relative error in the vessel caliber estimation is 2.93% with almost no bias. Moreover, the method can discriminate between arteries and catheter with an accuracy of 96.4%.
%P 496-503