Multi-scale line segmentation with automatic estimation of width, contrast and tangential direction in 2D and 3D medical images

Abstract

A new multi-scale segmentation technique for line-like structures in 2D and 3D medical images is presented. It is based on normalized first and second derivatives and on the eigenvector analysis of the hessian matrix. Application areas are the segmentation and tracking of bloodvessels, electrodes, catheters and other line-like objects. It allows for the estimation of the local diameter, the longitudinal direction and the contrast of the vessel and for the distinction between edge-like and line-like structures. The method is applicable as automatic 2D and 3D line-filter, as well as for interactive algorithms that are based on local direction estimation. A 3D line-tracker has been constructed that uses the estimated longitudinal direction as step-direction. After extraction of the centerline, the hull of the structure is determined by a 2D active-contour algorithm, applied in planes, orthogonal to the longitudinal line-direction. The procedure results in a stack of contours allowing quantitative crosssection area determination and visualization by means of a triangulation based rendering.