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Properly selected port sites for robot-assisted coronary artery bypass graft (CABG) improve the efficiency and quality of these procedures. In clinical practice, surgeons select port locations using external anatomic landmarks to estimate a patient's internal anatomy. This paper proposes an automated approach to port selection based on a preoperative image of the patient, thus avoiding the need to estimate internal anatomy. Using this image as input, port sites are chosen from a grid of surgeon-approved options by defining a performance measure for each possible port triad. This measure seeks to minimize the weighted squared deviation of the instrument and endoscope angles from their optimal orientations at each internal surgical site. This performance measure proves insensitive to perturbations in both its weighting factors and moderate intraoperative displacements of the patient's internal anatomy. A validation study of this port site selection algorithm was also performed. Six cardiac surgeons dissected model vessels using the port triad selected by this algorithm with performance compared to dissection using a surgeon-selected port triad and a port triad template described by Tabaie et al., 1999. With the algorithm-selected ports, dissection speed increased by up to 43% (p = 0.046) with less overall vessel trauma. Thus, this algorithmic approach to port site selection has important clinical implications for robot-assisted CABG which warrant further investigation.