Minimally invasive surgery of the beating heart can be associated with two major limitations: selecting port locations for optimal target coverage from x-rays and angiograms, and navigating instruments in a dynamic and confined 3D environment using only an endoscope. To supplement the current surgery planning and guidance strategies, we continue developing VCSP - a virtual reality, patient-specific, thoracic cavity model derived from 3D pre-procedural images. In this work, we apply elastic image registration to 4D cardiac images to model the dynamic heart. Our method is validated on two image modalities, and for different parts of the cardiac anatomy. In a helical CT dataset of an excised heart phantom, we found that the artificial motion of the epicardial surface can be extracted to within 0.93 ± 0.33 mm. For an MR dataset of a human volunteer, the error for different heart structures such as the myocardium, right and left atria, right ventricle, aorta, vena cava, and pulmonary artery, ranged from 1.08 ± 0.18 mm to 1.14 ± 0.22 mm. These results indicate that our method of modeling the motion of the heart is not only easily adaptable but also sufficiently accurate to meet the requirements for reliable cardiac surgery training, planning, and guidance.