Fast Segmentation of Abdominal Aortic Aneurysms for Endovascular Repair Planning and Follow-up

Authors: Iván Macía, María Arenas, Jon Haitz Legarreta, Isabelle Robin, Manuel Graña, Sabarinath Rajasekharan

Date: 01.10.2012


Abstract

Segmentation and quantification of AAAs in CTA images is a relevant task for primary diagnosis and follow-up after EVAR. This paper describes and evaluates a refined version of a fast and accurate method for the segmentation of the aneurysm thrombus based on a radial model approach. It uses a priori knowledge and spatial coherency for obtaining an initial thrombus contour which is then refined by removing spurious sectors. The method provides a fast segmentation and easy parameter setup while maintaining a high degree of accuracy, which makes it suitable for clinical routine. Thrombus segmentation results are presented in real clinical CTA images used for EVAR follow-up which demonstrate the high speed and accuracy of the method.

BIB_text

@Article {
author = {Iván Macía, María Arenas, Jon Haitz Legarreta, Isabelle Robin, Manuel Graña, Sabarinath Rajasekharan},
title = {Fast Segmentation of Abdominal Aortic Aneurysms for Endovascular Repair Planning and Follow-up},
pages = {72-79},
keywds = {

segmentation, medical imaging, thrombus, aorta, vessel, radial, fast, vascular, EVAR, follow-up


}
abstract = {

Segmentation and quantification of AAAs in CTA images is a relevant task for primary diagnosis and follow-up after EVAR. This paper describes and evaluates a refined version of a fast and accurate method for the segmentation of the aneurysm thrombus based on a radial model approach. It uses a priori knowledge and spatial coherency for obtaining an initial thrombus contour which is then refined by removing spurious sectors. The method provides a fast segmentation and easy parameter setup while maintaining a high degree of accuracy, which makes it suitable for clinical routine. Thrombus segmentation results are presented in real clinical CTA images used for EVAR follow-up which demonstrate the high speed and accuracy of the method.


}
date = {2012-10-01},
year = {2012},
}
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