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10.1109_access.2023.3318171.pdf (1.56 MB)

A Novel Approach to Monitor Head Movement Inside an MR Scanner Using Voltages Induced in Coils by Time-Varying Gradients

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submitted on 2024-02-18, 08:56 and posted on 2024-02-18, 08:56 authored by Enamul H. Bhuiyan, Muhammad E. H. Chowdhury, Paul M. Glover

To determine head pose within an MR scanner using measurements of gradient-induced voltage from a multiple coil. A practical implementation of this approach would involve measuring the position-sensitive voltages induced by the imaging gradients rather than additional gradient pulses. This would speed up the model formation phase and increase the temporal resolution of position monitoring. We propose a novel method to measure the gradient-induced voltages in a set of five coils to estimate the position and orientations (POS) into MR scanner. A training set of measurements was first made and then Principal Component Analysis (PCA) was applied to the POS data estimated by using Statistical Parametric Mapping (SPM8), and the principal components were collected into a design matrix. Experimental data were collected and then the coefficients derived from the training set were used to estimate the POS changes and the results compared to movement parameters found using image co-registration. The changes in POS estimated from SPM8 co-registration and from the measured voltages for the phantom and the subject. The differences in the positions were estimated by using SPM8 and the model relating the change in induced voltages to position. The range and root-mean-square (RMS) amplitude of these differences for the phantom/subject data. The results suggest that it is possible to estimate the position and orientation with 0.22mm and 0.24° root-mean-square error using this set-up. The new approach could be used for prospective or retrospective motion correction.

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Published in: IEEE Access
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Open Access funding provided by the Qatar National Library.



  • English



Publication Year

  • 2023

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License

Institution affiliated with

  • Qatar University
  • College of Engineering - QU