Automatic spatial calibration of ultra-low-field MRI for high-accuracy hybrid MEG-MRI

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Abstract

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. In the ULF MRI, the profiles are independent of the sample and therefore well-defined. In the most basic form, the spatial information of the profiles, captured in parallel ULF-MR acquisitions, is used to find the exact coordinate transformation required. We assessed our calibration method by simulations assuming a helmet-shaped pickup-coil-array geometry. Using a carefully constructed objective function and sufficient approximations, even with low-SNR images, sub-voxel and sub-millimeter calibration accuracy were achieved. After the calibration, distortion-free MRI and high spatial accuracy for MEG source localization can be achieved. For an accurate sensor-array geometry, the co-registration and associated errors are eliminated, and the positional error can be reduced to a negligible level.

Details

Original languageEnglish
Article number8672109
Pages (from-to)1317-1327
Number of pages11
JournalIEEE Transactions on Medical Imaging
Volume38
Issue number6
Publication statusPublished - 1 Jun 2019
MoE publication typeA1 Journal article-refereed

    Research areas

  • Calibration, Co-registration, Hybrid MEG-MRI, Magnetoencephalography, Sensitivity profile, Spatial accuracy, ULF MRI

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