In this paper we describe the generation of a geometric cardiac shape model based on cardiac CTA data. The model includes the four cardiac chambers and the trunks of the connected vasculature, as well as the coronary arteries and a set of cardiac landmarks. A mean geometric model for the end-diastolic heart has been built based on 27 end-diastolic cardiac CTA datasets and a mean motion model based on 11 multiphase datasets. The model has been evaluated with respect to its capability to estimate the position of cardiac structures. Allowing a similarity transformation to adapt the model to image data, cardiac surface positions can be predicted with an accuracy of below 5 mm.
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