Vessel surface reconstruction with a tubular deformable model

Abstract

Three-dimensional (3-D) angiographic methods are gaining acceptance for evaluation of atherosclerotic disease. However, measurement of vessel stenosis from 3-D angiographic methods can be problematic due to limited image resolution and contrast. We present a method for reconstructing vessel surfaces from 3-D angiographic methods that allows for objective measurement of vessel stenosis. The method is a deformable model that employs a tubular coordinate system. Vertex merging is incorporated into the coordinate system to maintain even vertex spacing and to avoid problems of self-intersection of the surface. The deformable model was evaluated on clinical magnetic resonance (MR) images of the carotid (n = 6) and renal (n = 2) arteries, on an MR image of a physical vascular phantom and on a digital vascular phantom. Only one gross error occurred for all clinical images. All reconstructed surfaces had a realistic, smooth appearance. For all segments of the physical vascular phantom, vessel radii from the surface reconstruction had an error of less than 0.2 of the average voxel dimension. Variability of manual initialization of the deformable model had negligible effect on the measurement of the degree of stenosis of the digital vascular phantom.

Level Set Based Surface Capturing in 3D Medical Images

“…Therefore, we will not place emphasis on the techniques of 3D reconstruction. Interested readers can consult [7,8,9] for details on surface reconstruction. As as an example, we applied a simple thresholding method followed by fast sweeping method [10] and nonlocal means surface smoothing [9] to reconstruct the surface represented by a level set function [11], which takes positive values inside the vessel region and negative values outside ( Fig.…”

3D models for vascular lumen segmentation in MRA images and for artery-stenting simulation

“…This approach overcomes the limitations of most existing methods (including [7]) based on 2D boundary extraction carried out independently in cross-sectional images along the vessel. Our method differs from [9] and [11] mainly by three characteristics: 1) it includes an automatic initialization of the vessel's centerline and of its approximate local diameters, 2) the model consists of two interacting components, a cylindrical surface and a centerline, hence no post-processing of the surface is necessary to deduce the final centerline, and 3) it is based on a different formalism: the simplex meshes [14]. Indeed, to model the internal wall of the vessel we use a cylindrical simplex surface mesh.…”

“…A patient-specific carotid artery model construction and the CFD simulation were carried out in another project [8], in which the vascular geometry was segmented using a tubular deformable mesh model [9]. To simulate the artery stenting, this mesh was merged with a cylindrical mesh model of the stent.…”

Modelling of blood flow resistance for an atherosclerotic artery with multiple stenoses and poststenotic dilatations

“…This data is collected by invasive or non-invasive means. Angiographic machinery [6,7,26] assesses the reduction in flow due to these obstructions so as to provide useful physiological data for cardiologists during cardiac diagnosis. Since the vessels are opaque to light, well established flow measurement techniques like laser Doppler velocimetry [21,10] or particle image velocimetry [10] cannot be applied.…”