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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Segmentation of Abdominal Aortic Aneurysms in CT Images Using a Radial Model Approach
verfasst von : Iván Macía, Jon Haitz Legarreta, Céline Paloc, Manuel Graña, Josu Maiora, Guillermo García, Mariano de Blas
Erschienen in: Intelligent Data Engineering and Automated Learning - IDEAL 2009
Verlag: Springer Berlin Heidelberg
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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 leads to 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.