Basis function compression for field probe monitoring

Field monitoring using field probes allows for accurate measurement of magnetic field perturbations, such as from eddy currents, during MRI scanning. However, errors may result when the spatial variation of the fields is not well-described by the conventionally used spherical harmonics model that has the maximum order constrained by the number of probes. The objective of this work was to develop and validate a field monitoring approach that compresses higher order spherical harmonics into a smaller set of new basis functions that can be characterized using fewer probes.

Field monitoring of acquisitions was repeated with probes in different locations. High-order field dynamics were computed from this "calibration" data assembled from provided scans, from which compression matrices could be devised using principal component analysis. Compression matrices were then used to fit field dynamics using "compressed" basis functions with data from 16 probes, which were then used in image reconstruction. Performance was evaluated by assessing the accuracy of computed field dynamics as well as in vivo image quality. Technique generalizability was also assessed by using various acquisition and diffusion encoding strategies in the calibration.

Qualitative and quantitative improvements in accuracy were observed when using the proposed fitting method compared to the conventional approach. However, compression effectiveness was influenced by the probe quantity and arrangement, and the specific acquisition data included in the calibration.

The ability to tailor basis functions to more compactly describe the spatial variation of field perturbations enables improved characterization of fields with rapid spatial variations.