Exploring Interaction Paradigms for Performing Medical Image Segmentation Tasks in Virtual Reality

Virtual reality (VR) facilitates immersive visualization and interaction with complex medical images in immersive platforms. It remains unclear which VR input schemes and devices are optimal for these tasks. In this study, we perform a 12-person study to investigate user performance and experience while performing medical image segmentation with two control schemes, keyboard and mouse (KBM) and VR motion controllers (MC). Our results showed that motion controllers are faster in smaller segmentation tasks and offer a more pleasant user experience, however no significant difference in user accuracy was observed.