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Coronary Artery Tracking from Dynamic Cardiac CT Sequences

In this paper, we present an algorithm for coronary artery segmentation and tracking in dynamic cardiac CT sequences. The algorithm allows the automatic construction of a 4D coronary motion model from pre-operative CT which can be used for guiding totally-endoscopic coronary artery bypass surgery (TECAB). The A* graph search algorithm is used for tracking the coronary arteries through different time frames automatically. First, a Hessianbased vesselness filter is used to enhance tubular-like sturcture in the cardiac CT images. Then a smooth window function is used to highlight the intensity region where the coronaries appear. A cost function is constructed based on vesselness and intensity information. A common problem in dynamic cardiac CT is reconstruction artifacts occuring due to the cardiac and respiratory motion. To enable the tracking of the coronaries in these cases we use prior probability information from previous time frames to increase the robustness of the tracking. We have validated the accuracy of the proposed tracking algorithm by comparing the automatically tracked centerlines of the coronaries in each time frame with the manually extracted coronary centerlines. The average error of the tracking is 0.82mm for CT sequences I, 0.85mm for CT sequences II.