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Automatic coregistration of MRI and on-scalp MEG
- Source :
- Journal of neuroscience methods. 358
- Publication Year :
- 2021
-
Abstract
- Background Recent progress in optically pumped magnetometers (OPMs) and high-temperature superconducting quantum interference devices (SQUIDs) has facilitated the development of an on-scalp magnetoencephalography (MEG) system that offers high signal intensity and flexibility at a lower cost. While the on-scalp sensor array has high flexibility, it brings new challenges to accurate sensor-to-brain coregistration, which is essential for MEG source localization. New method A novel automatic filtering algorithm based on plane segmentation was proposed to locate on-scalp MEG sensors in 3D images reconstructed from optical scanning. Global image registration was employed for the automatic alignment of anatomical images and sensor positions. Results Seventy-one sensor dummies on the scalp were located and registered to brain anatomical images. The deviations of the sensor location and orientation from the averaged result of 10 measurements were less than 1 mm and 0.6°, respectively. The entire process could be completed in less than 4 min. Comparison with existing methods Compared with existing methods that involve various manual procedures, such as moving digitizers to fiducials and repeatedly pulling out sensors, our proposed coregistration method is more efficient and accurate. Conclusion An automatic method for the coregistration of anatomical structure and on-scalp sensors that will have a large impact on the practical use of on-scalp MEG is developed.
- Subjects :
- 0301 basic medicine
Magnetometer
Computer science
Image registration
law.invention
03 medical and health sciences
0302 clinical medicine
Sensor array
law
medicine
Computer vision
Brain Mapping
Scalp
medicine.diagnostic_test
Orientation (computer vision)
business.industry
General Neuroscience
Process (computing)
Brain
Magnetoencephalography
Magnetic Resonance Imaging
030104 developmental biology
medicine.anatomical_structure
Artificial intelligence
business
Fiducial marker
030217 neurology & neurosurgery
Subjects
Details
- ISSN :
- 1872678X
- Volume :
- 358
- Database :
- OpenAIRE
- Journal :
- Journal of neuroscience methods
- Accession number :
- edsair.doi.dedup.....bae5b391d05a6edea6cc10d04efac6a2