Pregled bibliografske jedinice broj: 49721
3-D image analysis of abdominal aortic aneurysm
3-D image analysis of abdominal aortic aneurysm // Medical Infobahn for Europe / / Hasman, A. ; Blobel, B. ; Dudeck, J. ; Engelbrecht, R. ; Gell, G. (ur.).
Hannover, Njemačka: IOS Press, 2000. str. 1195-1200 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 49721 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
3-D image analysis of abdominal aortic aneurysm
Autori
Subašić, Marko ; Lončarić, Sven ; Sorantin, Erich
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Medical Infobahn for Europe
/ / Hasman, A. ; Blobel, B. ; Dudeck, J. ; Engelbrecht, R. ; Gell, G. - : IOS Press, 2000, 1195-1200
Skup
MIE2000 and GMDS2000
Mjesto i datum
Hannover, Njemačka, 27.08.2000. - 01.09.2000
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
3-D image analysis; deformable models; level set; image segmentation
Sažetak
In this paper we propose a technique for 3-D segmentation of abdominal aortic aneurysm (AAA) from computed tomography (CT) angiography images. Output data form the proposed method can be used for measurement of aortic shape and dimensions. Knowledge of aortic shape and size is very important for selection of appropriate stent graft device for treatment of AAA. The technique is based on a 3-D deformable model and utilizes the level-set algorithm for implementation of the method. The method performs 3?D segmentation of CT images and extracts a 3-D model of aortic wall. Once the 3-D model of aortic wall is available it is easy to perform all required measurements for appropriate stent graft selection. The method proposed in this paper uses the level-set algorithm instead of the classical active contour algorithm developed by Kass et al. The main advantage of the level set algorithm is that it enables easy segmentation surpassing most of the drawbacks of the classical approach. In the level-set approach for shape modeling, a 3-D surface is represented by a real 3-D function or equivalent 4-D surface. The 4-D surface is then evolved through an iterative process of solving the differential equation of surface motion. Surface motion is defined by velocity at each point. The velocity is a sum of constant velocity and curvature-dependent velocity. The stopping criterion is calculated based on image gradient. The algorithm has been implemented in MATLAB and C languages. Experiments have been performed using real patient CT angiography images and have shown good results.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
