Model-based detection of tubular structures in 3D images

Detection of tubular structures in 3D images is an important issue for vasc ular medical imaging. We present in this paper a new approach for centerlin e detection and reconstruction of 3D tubular structures. Several models of vessels are introduced for estimating the sensitivity of the image second-o rder derivatives according to elliptical cross section, to curvature of the axis, or to partial volume effects. Our approach uses a multiscale analysi s for extracting vessels of different sizes according to the scale. For a g iven 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 synth etic images, an image of a phantom, and real images, with encouraging resul ts. (C) 2000 Academic Press.