Detection of tubular structures in 3D images is an important issue for vascular medical imaging. We present in this paper a new approach for centerline detection and reconstruction of 3D tubular structures. Several models of vessels are introduced for estimating the sensitivity of the image second-order derivatives according to elliptical cross section, to curvature of the axis, or to partial volume effects. Our approach uses a multiscale analysis for extracting vessels of different sizes according to the scale. For a given model of vessel, we derive an analytic expression of the relationship between the radius of the structure and the scale at which it is detected. The algorithm gives both centerline extraction and radius estimation of the vessels allowing their reconstruction. The method has been tested on synthetic images, an image of a phantom, and real images, with encouraging results.

Abstract-Cardiovascular diseases remain the primary cause of death in developed countries. In most cases, exploration of possibly underlying coronary artery pathologies is performed using X-ray coronary angiography. Current clinical routine in coronary angiography is directly conducted in 2-D projection images from several static viewing angles. However, for diagnosis and treatment purposes, coronary artery reconstruction is highly suitable. The purpose of this study is to provide physicians with a 3-D model of coronary arteries, e.g. for absolute threedimensional measures for lesion assessment, instead of direct projective measures deduced from the images, which are highly dependent on the viewing angle. In this article, we propose a novel method to reconstruct coronary arteries from one single rotational X-ray projection sequence. As a side result, we also obtain an estimation of the coronary artery motion. Our method consists of 3 main consecutive steps: (1) 3-D reconstruction of coronary artery centerlines, including respiratory motion compensation, (2) coronary artery 4-D motion computation, and (3) 3-D tomographic reconstruction of coronary arteries, involving compensation for respiratory and cardiac motions. We present some experiments on clinical datasets, and the feasibility of a true 3-D Quantitative Coronary Analysis is demonstrated.

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Three-dimensional DSA is valuable for evaluating the potential for EVT, finding a working view, and performing accurate measurements.

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