Landmark-based mixed-reality perceptual alignment of medical imaging data and accuracy validation in living subjects - Leuze, Christoph; Sathyanarayana, Supriya; Daniel, Bruce L; McNab, Jennifer A (2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2020)
Medical augmented reality (AR) applications where virtual renderings are aligned with the real world allow to visualize internal anatomy of the patient to a medical caregiver wearing an AR headset. Accurate alignment of virtual and real content is important for applications where the virtual rendering is used to guide the medical procedure such as a surgery. Compared to 2D AR applications, where the alignment accuracy can be directly measured on the 2D screen, 3D medical AR applications require alignment measurements using phantoms and external tracking systems. In this paper we present an approach for landmark-based alignment, validation and accuracy measurement of a 3D AR overlay of medical images on the real-world subject. This is done by performing an initial MRI of a subject's head, an AR alignment task of the virtual rendering of the head MRI data to the subject's real-world head using virtual fiducials, and a second MRI scan to test the accuracy of the AR alignment task. We have performed these 3D medical AR alignment measurements on seven volunteers using a MagicLeap AR head-mounted display. Across all seven volunteers we measured an alignment accuracy of 4.7 ± 2.6 mm. These results suggest that such an AR application can be a valuable tool for guiding non-invasive transcranial magnetic brain stimulation treatment. The presented MRI-based accuracy validation will furthermore be an important versatile tool to establish the safety of medical AR techniques.