%0 Conference Paper %1 Macia2009 %A Macia, Ivan %A Legarreta, Jon Haitz %A Paloc, Celine %A Grana, Manuel %A Maiora, Josu %A Garcia, Guillermo %A de Blas, Mariano %B Intelligent Data Engineering and Automated Learning, Proceedings %D 2009 %E Corchado, E and Yin, H, %I Springer-Verlag Berlin %K aneurysm aneurysm; aortic endovascular functions} growing; image moments; radial region repair; segmentation; {abdominal %P 664-671 %T Segmentation of Abdominal Aortic Aneurysms in CT Images Using a Radial Model Approach %V 5788 %X 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. %@ 978-3-642-04393-2

@inproceedings{Macia2009, 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 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.}}, added-at = {2011-03-11T12:21:24.000+0100}, affiliation = {{Macia, I (Reprint Author), Vicomtech, Biomed Applicat Dept, Donostia San Sebastian, Spain. {[}Macia, Ivan; Haitz Legarreta, Jon; Paloc, Celine] Vicomtech, Biomed Applicat Dept, Donostia San Sebastian, Spain.}}, author = {Macia, Ivan and Legarreta, Jon Haitz and Paloc, Celine and Grana, Manuel and Maiora, Josu and Garcia, Guillermo and de Blas, Mariano}, biburl = {https://www.bibsonomy.org/bibtex/2055421678c7c572ca6b5d0e3dce627a2/jmaiora}, booktitle = {{Intelligent Data Engineering and Automated Learning, Proceedings}}, doc-delivery-number = {{BND11}}, editor = {{Corchado, E and Yin, H}}, interhash = {8dee2bbf7867d08f8b3aeaf22b820e31}, intrahash = {055421678c7c572ca6b5d0e3dce627a2}, isbn = {{978-3-642-04393-2}}, issn = {{0302-9743}}, keywords = {aneurysm aneurysm; aortic endovascular functions} growing; image moments; radial region repair; segmentation; {abdominal}, language = {{English}}, number-of-cited-references = {{7}}, owner = {Josu}, pages = {{664-671}}, publisher = {{Springer-Verlag Berlin}}, series = {{Lecture Notes in Computer Science}}, subject-category = {{Computer Science, Theory \& Methods}}, times-cited = {{0}}, timestamp = {2011-03-11T12:21:26.000+0100}, title = {{Segmentation of Abdominal Aortic Aneurysms in CT Images Using a Radial Model Approach}}, type = {{Proceedings Paper}}, unique-id = {{ISI:000274188700081}}, volume = {{5788}}, year = {{2009}} }