Segmentation of Abdominal Aortic Aneurysms in CT Images Using a Radial Model Approach
Egileak: Iván Macía and Jon Haitz Legarreta and Céline Paloc and Manuel Graña and Josu Maiora and Guillermo García and Mariano de Blas
Data: 23.09.2009
Abstract
BIB_text
author = {Iván Macía and Jon Haitz Legarreta and Céline Paloc and Manuel Graña and Josu Maiora and Guillermo García and Mariano de Blas},
title = {Segmentation of Abdominal Aortic Aneurysms in CT Images Using a Radial Model Approach},
pages = {664-671},
volume = {5788},
keywds = {
segmentation, aorta, aneurysm, radial model, CT, image processing, medical imaging
}
abstract = {
Abdominal Aortic Aneurysm (AAA) is a dangerous condition where the weakening of the aortic wall leads to its deformation and the generation of a thrombus. To prevent a possible rupture of the aortic wall, AAAs can be treated non-invasively by means of the Endovascular Aneurysm Repair Technique (EVAR), which consists of placing a stent-graft inside the aorta in order to exclude the bulge from the blood circulation and usually results in its contraction. Nevertheless, the bulge may continue to grow without any apparent leak. In order to effectively assess the changes experienced after surgery, it is necessary to segment the aneurysm, which is a very time-consuming task. Here we describe the initial results of a novel model-based approach for the semi-automatic segmentation of both the lumen and the thrombus of AAAs, using radial functions constrained by a priori knowledge and spatial coherency.
}
isbn = {978-3-642-04393-2},
date = {2009-09-23},
year = {2009},
}