Abstract
BackgroundThe effective geometric modeling of vascular structures is crucial for diagnosis, therapy planning and medical education. These applications require good balance with respect to surface smoothness, surface accuracy, triangle quality and surface size.MethodsOur method first extracts the vascular boundary voxels from the segmentation result, and utilizes these voxels to build a three-dimensional (3D) point cloud whose normal vectors are estimated via covariance analysis. Then a 3D implicit indicator function is computed from the oriented 3D point cloud by solving a Poisson equation. Finally the vessel surface is generated by a proposed adaptive polygonization algorithm for explicit 3D visualization.ResultsExperiments carried out on several typical vascular structures demonstrate that the presented method yields both a smooth morphologically correct and a topologically preserved two-manifold surface, which is scale-adaptive to the local curvature of the surface. Furthermore, the presented method produces fewer and better-shaped triangles with satisfactory surface quality and accuracy.ConclusionsCompared to other state-of-the-art approaches, our method reaches good balance in terms of smoothness, accuracy, triangle quality and surface size. The vessel surfaces produced by our method are suitable for applications such as computational fluid dynamics simulations and real-time virtual interventional surgery.
Highlights
The effective geometric modeling of vascular structures is crucial for diagnosis, therapy planning and medical education
We evaluated our method in terms of surface smoothness, surface accuracy, triangle quality, surface size and efficiency on the tested dataset
Since the surfaces produced by Marching Cubes (MC), multi-level partition unity (MPU)-based and our method are all triangular meshes, for the convenience of comparison, we applied the Loop scheme [27] with three iterations to produce vessel surface
Summary
The effective geometric modeling of vascular structures is crucial for diagnosis, therapy planning and medical education These applications require good balance with respect to surface smoothness, surface accuracy, triangle quality and surface size. The smoothness of the surface produced by these methods is poor, especially where the vessel branches At these points, transition is unavoidably discontinuous and has significant artifacts, resulting in very low visual quality. To achieve high-quality surface, other advanced surface representations have been investigated, such as, B-spline surfaces [8], simplex meshes [9], convolution surfaces [10], and subdivision surfaces [11,12] Most of these methods yield desirable smooth surfaces; they suffer from low accuracy, badly shaped triangles or a large number of polygons
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