Motion tracking of left ventricle and coronaries in 4D CTA

Abstract

In this paper, we present a novel approach for simultaneous motion tracking of left ventricle and coronary arteries from cardiac Computed Tomography Angiography (CTA) images. We first use the multi-scale vesselness filter proposed by Frangi et al . 1 to enhance vessels in the cardiac CTA images. The vessel centrelines are then extracted as the minimal cost path from the enhanced images. The centrelines at end-diastolic (ED) are used as prior input for the motion tracking. All other centrelines are used to evaluate the accuracy of the motion tracking. To segment the left ventricle automatically, we perform three levels of registration using a cardiac atlas obtained from MR images. The cardiac motion is derived from cardiac CTA sequences by using local-phase information to derive a non-rigid registration algorithm. The CTA image at each time frame is registered to the ED frame by maximising the proposed similarity function and following a serial registration scheme. Once the images have been aligned, a dynamic motion model of the left ventricle can be obtained by applying the computed free-form deformations to the segmented left ventricle at ED phase. A similar propagation method also applies to the coronary arteries. To validate the accuracy of the motion model we compare the actual position of the coronaries and left ventricle in each time frame with the predicted ones as estimated from the proposed tracking method.