The use of 3D printed models of the right ventricular outflow tract (RVOT) for surgical and interventional planning is growing and often requires image segmentation of cardiac magnetic resonance (CMR) images. Segmentation results may vary based on contrast, image sequence, signal threshold chosen by the operator, and manual post-processing. The purpose of this study was to determine potential biases and post-processing errors in image segmentation to enable informed decisions. Models of the RVOT and pulmonary arteries from twelve patients who had contrast enhanced CMR angiography with gadopentetate dimeglumine (GPD), gadofosveset trisodium (GFT), and a post-GFT inversion-recovery (IR) whole heart sequence were segmented, trimmed, and aligned by three operators. Geometric agreement and minimal RVOT diameters were compared between sequences and operators. To determine the contribution of threshold, interoperator variability was compared between models created by the same two operators using the same versus different thresholds. Geometric agreement by Dice between objects was high (intraoperator: 0.89–0.95; interoperator: 0.95–0.97), without differences between sequences. Minimal RVOT diameters differed on average by − 1.9 to − 1.3 mm (intraoperator) and by 0.4 to 1.4 mm (interoperator). The contribution of threshold to interoperator geometric agreement was not significant (same threshold: 0.96 ± 0.06, different threshold: 0.93 ± 0.05; p = 0.181), but minimal RVOT diameters were more variable with different versus constant thresholds (− 9.12% vs. 2.42%; p < 0.05). Thresholding does not significantly change interoperator variability for geometric agreement, but does for minimal RVOT diameter. Minimal RVOT diameters showed clinically relevant variation within and between operators.