Automatic co-registration of OPM-MEG and MRI using a 3D laser scanner

Abstract

Small and lightweight optically pumped magnetometers (OPMs) have led to the development of wearable magnetoencephalography (MEG). Wearable and flexible configuration features are the highlights of OPMs; however, they present challenges for MEG and magnetic resonance imaging (MRI) co-registration. The co-registration of MEG and MRI is a precondition for source localization and significantly affects the spatial accuracy of source localization. In this study, we proposed an automatic algorithm for co-registration, which consists of two parts: helmet-to-head registration and head-to-MRI registration. For helmet-to-head registration, a fast point feature histogram (FPFH) descriptor was used to determine the sensor locations and orientations on the scanned data. For head-to-MRI registration, the nose region was precisely cropped and aligned. The results showed that the algorithm has excellent performance in speed (average time of 15 s) and accuracy (rotation error of 0.15∘ and translation error of 0.29 mm), which is the highest accuracy in relevant research.