This document describes a novel scheme for the automated extraction of the central lumen lines of coronary arteries from computed tomography angiography (CTA) data. The scheme first obtains a seg- mentation of the whole coronary tree and subsequently extracts the centerlines from this segmentation. The first steps of the segmentation algorithm consist of the detection of the aorta and the entire heart region. Next, candidate coronary artery components are detected in the heart region after the masking of the cardiac blood pools. Based on their location and geometrical properties the structures representing the right and left arterties are selected from the candidate list. Starting from the aorta, connections between these structures are made resulting in a final segmentation of the whole coronary artery tree, A fast-marching level set method combined with a backtracking algorithm is employed to obtain the initial centerlines within this segmentation. For all vessels a curved multiplanar reformatted image (CMPR) is constructed and used to detect the lumen contours. The final centerline was then defined by determining the center of gravity of the detected lumen in the transversal CMPR slices. Within the scope of the MICCAI Challenge "Coronary Artery Tracking 2008", the coronary tree segmentation and centerline extraction scheme was used to automatically detect a set of centerlines in 24 datasets. For 8 data sets reference centerlines were available. This training data was used during the development and tuning of the algorithm. Sixteen other data sets were provided as testing data. Evaluation of the proposed methodology was performed through submission of the resulting centerlines to the MICCAI Challenge website