3-D deformable model for aortic aneurysm segmentation from CT images

For treatment of abdominal aortic aneurysm (AAA) by placement of aortic stent graft device it is necessary to make accurate AAA measurements in order to choose the stent graft device of appropriate shape and size. Here, the authors propose a novel technique for 3-D segmentation of abdominal aortic aneurysm from computed tomography (CT) angiography images. The technique is based on 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 AAA model. Once the 3-D model of AAA is available it is easy to perform all required measurements for appropriate stent graft selection. The method proposed here uses the level-set algorithm instead of the classical active contour algorithm developed by Kass et al. (1987). The main advantage of the level set algorithm is that it enables easy segmentation of complex structures such as bifurcations in arteries. In the level set approach for shape modeling, a 3-D surface is represented by a real 3-D function that can be viewed as a 4-D surface. The 4-D surface evolves through an iterative process of solving the differential equation of surface motion. The surface motion is defined by velocity at each point. The velocity is a sum of a constant velocity (inflation force), curvature-dependent velocity (internal force), and image-dependent velocity (external force). The image-dependent velocity is computed on the basis of 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. A 3-D rendering of the segmented region is performed that is useful for aneurysm shape visualization