Background Electrocardiographic imaging (ECGI) is a promising tool for the treatment and diagnosis of cardiac arrhythmias. ECGI estimates non-invasively the electrical activity of the heart using body surface potentials (BSPs) obtained at the body surface in combination with a specific CT/MRI based anatomical models and defined electrode positions. In order to solve the ECGI inverse problem the first step to be considered is indeed the image segmentation and mesh generation. Objective Our main purpose is to evaluate the effect of the inter-operator segmentation variability on the PVC localization. Methods Eight different cardiac segmentations from the same single subject CT-scans were performed by researchers within the consortium for Electrocardiographic Imaging. For all generated meshes, eight ventricular stimulation protocols were used; left and right ventricular free walls (LV, RV), apex, left and right ventricular outflow tract (LVOT, RVOT), septum, and two locations at the left and right heart base (LVB, RVB). BSPs were generated using computational models. We designed two test cases: with and without segmentation uncertainty. In test A, no segmentation uncertainty is considered. In test B, we solve the inverse problem for the eight geometries starting from one single BSP generated with a reference heart geometry. For each test case and for each stimulation protocol we computed the inverse solution using the Method of Fundamental Solutions and assessed the Localization Error (LE) of the pacing sites. In order to quantify the effect of segmentation uncertainty we also computed the difference between LEs obtained in tests B and A. Results In test A, the mean LEs for LV, RV, apex, LVOT, RVOT, septum, LVB and RVB pacings are 7, 7, 5, 12, 14, 18, 13, 15 mm, respectively. In test B, the mean LEs are 7, 7, 5, 17, 23, 17, 16, 23 mm, respectively. The average differences between LEs are 0, 0, -1,5, 8, -1, 3, 8 mm, respectively. Conclusion This study shows that the effect of the segmentation uncertainty on the localization of PVC is more important for RVOT, LVOT, RVB and LVB. We believe that the high uncertainty is due to the variability of segmentations at the base of the heart. These findings suggest that uncertainty in cardiac segmentation can have a significant impact on ECGI and its interpretability in clinical applications; therefore, careful segmentation is strongly recommended, especially at the base of the heart.