Automated mitral valve vortex ring evolution analysis from magnetic resonance 4D flow data is feasible. However, time-consuming manual segmentation of the left ventricular blood pool represents a bottleneck. We simulated speed-up and variability of manual segmentation and analyzed the impact on vortex ring parameters. Automated mitral valve vortex ring extraction and analysis yielded robust results, even when applying the end-diastolic segmentation mask to all cardiac phases. Error analysis of vortex ring parameters showed that under-segmentation of the ventricular blood pool should be avoided. Speeding up segmentation by using only the end-diastolic mask enables clinical mitral valve vortex ring analysis studies.