In this paper we present a method for coronary artery motion tracking in 4D cardiac CT data sets. 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 proposed approach is based on two steps: In the first step, the coronary arteries are extracted in the end-diastolic time frame using a minimal cost path approach. To achieve this, the start and end points of the coronaries are identified interactively and the minimal cost path between the start and end points is computed using the A* graph algorithm. In the second stage the coronaries are tracked automatically through all other phases of the cardiac cycle. This is achieved by automatically identifying the start and end points in subsequent time points through a non-rigid template-tracking algorithm. Once the start and end points have been located, the minimal cost path is constructed in every time frame. We compare the proposed approach to two alternative approaches: The first one is based on a semi-automatic extraction of the coronaries with start and end points manually supplied in each time frame and the second approach is based on propagating the extracted coronaries from the end-diastolic time frame to other time frames using non-rigid registration. Our results show that the proposed approach performs significantly better than non-rigid registration based method and that the resulting motion model is comparable to the motion model constructed from semi-automatic extractions of the coronaries.

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7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010
Department of Cardiology

Zhang, D. P., Risser, L., Metz, C., Neefjes, L., Mollet, N., Niessen, W., & Rueckert, D. (2010). Coronary artery motion modeling from 3D cardiac CT sequences using template matching and graph search. Presented at the 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010. doi:10.1109/ISBI.2010.5490171