Automated extraction of vascular information from angiographic images using a vessel-tracking algorithm

Abstract
We are developing an automated method for tracking the entire vascular tree in x-ray angiographic images. The vascular tree information which is obtained by our tracking method can be used for automated analyses of angiographic images such as detection and quantitation of vascular lesions identification of regions related to diseased vessels reconstruction of 3D representations from biplane images and analysis of blood flow. Our tracking method incorporates an efficient way of sampling the image data a connectivity test to assure that the tracking follows paths which are within vascular segments and a guided-search method in which information from nearby regions of the image is used to guide the tracking. Our current tracking method is more robust than a previous method and is capable of accurately tracking complex vascular trees which include tortuous vessels.