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Intra-coronary optical coherence tomography (OCT) provides ultra-high resolution imaging of coronary vessel wall structures. However, during image acquisition the OCT catheter is affected by cardiac motion. These motion-induced artifacts not only complicate longitudinal image reconstructions, it results in a saw-tooth shaped appearance of the coronary vessel wall, but more importantly it affects the accuracy of quantitative analysis (QOCT). To overcome this problem we propose to perform image-based gating applying a genetic algorithm (GA) that automatically selects a subset of OCT cross-sections that are relatively unaffected by the catheter displacement during the cardiac cycle. The gated subset contains cross-sections (frames) acquired in the near end-diastolic phase, during which the heart is relatively motionless. We evaluated the GA in a comparison test with a different gating method (Simulated Annealing (SA)) and with manual frame selection (MFS) and found promising results.