Accuracy in localizing the brain areas that generate neuromagnetic activity in magnetoencephalography (MEG) is dependent on properly co-registering MEG data to the participant's structural magnetic resonance image (MRI). Effective MEG-MRI co-registration is, in turn, dependent on how accurately we can digitize anatomical landmarks on the surface of the head. In this study, we compared the performance of three devices-Polhemus electromagnetic system, NextEngine laser scanner and Microsoft Kinect for Windows-for source localization accuracy and MEG-MRI co-registration. A calibrated phantom was used for verifying the source localization accuracy. The Kinect improved source localization accuracy over the Polhemus and the laser scanner by 2.23 mm (137%) and 0.81 mm (50%), respectively. MEG-MRI co-registration accuracy was verified on data from five healthy human participants, who received the digitization process using all three devices. The Kinect device captured approximately 2000 times more surface points than the Polhemus in one third of the time (1 min compared to 3 min) and thrice as many points as the NextEngine laser scanner. Following automated surface matching, the calculated mean MEG-MRI co-registration error for the Kinect was improved by 2.85 mm with respect to the Polhemus device, and equivalent to the laser scanner. Importantly, the Kinect device automatically aligns 20-30 images per second in real-time, reducing the limitations on participant head movement during digitization that are implicit in the NextEngine laser scan (~1 min). We conclude that the Kinect scanner is an effective device for head digitization in MEG, providing the necessary accuracy in source localization and MEG-MRI co-registration, while reducing digitization time.
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http://dx.doi.org/10.3389/fnins.2014.00326 | DOI Listing |
Neuroimage
August 2019
Department of Neuroscience, Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, via dei Vestini 31, 66100 Chieti, Italy; Institute for Advanced Biomedical Technologies, G. d'Annunzio University of Chieti-Pescara, via dei Vestini 31, 66100 Chieti, Italy.
Co-registration between structural head images and functional MEG data is needed for anatomically-informed MEG data analysis. Despite the efforts to minimize the co-registration error, conventional landmark- and surface-based strategies for co-registering head and MEG device coordinates achieve an accuracy of typically 5-10 mm. Recent advances in instrumentation and technical solutions, such as the development of hybrid ultra-low-field (ULF) MRI-MEG devices or the use of 3D-printed individualized foam head-casts, promise unprecedented co-registration accuracy, i.
View Article and Find Full Text PDFIEEE Trans Med Imaging
June 2019
With a hybrid magnetoencephalography (MEG)-MRI device that uses the same sensors for both modalities, the co-registration of MRI and MEG data can be replaced by an automatic calibration step. Based on the highly accurate signal model of ultra-low-field (ULF) MRI, we introduce a calibration method that eliminates the error sources of traditional co-registration. The signal model includes complex sensitivity profiles of the superconducting pickup coils.
View Article and Find Full Text PDFFront Neurosci
November 2014
Biomedical Translational Imaging Centre (BIOTIC), IWK Health Centre Halifax, NS, Canada ; Faculty of Computer Science, Dalhousie University Halifax, NS, Canada.
Accuracy in localizing the brain areas that generate neuromagnetic activity in magnetoencephalography (MEG) is dependent on properly co-registering MEG data to the participant's structural magnetic resonance image (MRI). Effective MEG-MRI co-registration is, in turn, dependent on how accurately we can digitize anatomical landmarks on the surface of the head. In this study, we compared the performance of three devices-Polhemus electromagnetic system, NextEngine laser scanner and Microsoft Kinect for Windows-for source localization accuracy and MEG-MRI co-registration.
View Article and Find Full Text PDFClin Neurophysiol
December 2014
Department of Clinical Neurophysiology, Neurological Institute, Faculty of Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Objective: Co-registration between the head shape extracted from anatomical images that are obtained using a 3D digitizer is a non-negligible factor for magnetoencephalographic (MEG) utilization. The study aimed to propose a novel quick system based on a laser scanning technique involving a 3D laser scanner system that allows instant measurement while maintaining high accuracy and reproducibility.
Methods: The measurement duration, accuracy, and reproducibility of the finger representations in response to tactile stimulation between the 3D laser scanner-based method and the conventional magnetic field digitizer-based method were compared in 11 healthy subjects.
Exp Brain Res
March 2009
Institute for Biomagnetism and Biosignalanalysis, University of Muenster, Münster, Germany.
Synthetic aperture magnetometry (SAM) is a powerful MEG source localization method to analyze evoked as well as induced brain activity. To gain structural information of the underlying sources, especially in group studies, individual magnetic resonance images (MRI) are required for co-registration. During the last few years, the relevance of MEG measurements on understanding the pathophysiology of different diseases has noticeable increased.
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