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1.
Comput Math Methods Med ; 2015: 202539, 2015.
Article in English | MEDLINE | ID: mdl-26236390

ABSTRACT

A correct patient-specific identification of the abdominal aortic aneurysm is useful for both diagnosis and treatment stages, as it locates the disease and represents its geometry. The actual thickness and shape of the arterial wall and the intraluminal thrombus are of great importance when predicting the rupture of the abdominal aortic aneurysms. The authors describe a novel method for delineating both the internal and external contours of the aortic wall, which allows distinguishing between vessel wall and intraluminal thrombus. The method is based on active shape model and texture statistical information. The method was validated with eight MR patient studies. There was high correspondence between automatic and manual measurements for the vessel wall area. Resulting segmented images presented a mean Dice coefficient with respect to manual segmentations of 0.88 and a mean modified Hausdorff distance of 1.14 mm for the internal face and 0.86 and 1.33 mm for the external face of the arterial wall. Preliminary results of the segmentation show high correspondence between automatic and manual measurements for the vessel wall and thrombus areas. However, since the dataset is small the conclusions cannot be generalized.


Subject(s)
Aortic Aneurysm, Abdominal/diagnosis , Aortic Aneurysm, Abdominal/pathology , Blood Vessels/pathology , Endothelium, Vascular/pathology , Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging , Thrombosis/pathology , Algorithms , Angiography , Biomechanical Phenomena , Humans , Imaging, Three-Dimensional , Models, Statistical , Reproducibility of Results , Software , Thrombosis/diagnosis , Tomography, X-Ray Computed
2.
Med Biol Eng Comput ; 52(2): 159-68, 2014 Feb.
Article in English | MEDLINE | ID: mdl-24306943

ABSTRACT

In order to perform finite element (FE) analyses of patient-specific abdominal aortic aneurysms, geometries derived from medical images must be meshed with suitable elements. We propose a semi-automatic method for generating conforming hexahedral meshes directly from contours segmented from medical images. Magnetic resonance images are generated using a protocol developed to give the abdominal aorta high contrast against the surrounding soft tissue. These data allow us to distinguish between the different structures of interest. We build novel quadrilateral meshes for each surface of the sectioned geometry and generate conforming hexahedral meshes by combining the quadrilateral meshes. The three-layered morphology of both the arterial wall and thrombus is incorporated using parameters determined from experiments. We demonstrate the quality of our patient-specific meshes using the element Scaled Jacobian. The method efficiently generates high-quality elements suitable for FE analysis, even in the bifurcation region of the aorta into the iliac arteries. For example, hexahedral meshes of up to 125,000 elements are generated in less than 130 s, with 94.8 % of elements well suited for FE analysis. We provide novel input for simulations by independently meshing both the arterial wall and intraluminal thrombus of the aneurysm, and their respective layered morphologies.


Subject(s)
Aortic Aneurysm, Abdominal/diagnosis , Thrombosis/diagnosis , Algorithms , Aorta/pathology , Aortic Aneurysm, Abdominal/pathology , Computer Simulation , Finite Element Analysis , Humans , Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Software , Thrombosis/pathology
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