Basis function compression for field probe monitoring

TL;DR

This paper introduces a method to compress higher order spherical harmonic basis functions into a smaller set, enabling accurate field monitoring with fewer probes during MRI scans, thus improving magnetic field characterization.

Contribution

The work develops a novel basis function compression technique using principal component analysis to enhance field monitoring efficiency with fewer probes.

Findings

Improved accuracy in field dynamics estimation using compressed basis functions.

Compression effectiveness varies with calibration data used.

Enhanced MRI image quality through better field perturbation modeling.

Abstract

Purpose: 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 harmonic basis functions into a smaller set of new basis functions that can be computed from fewer probes. Methods: Field monitoring of acquisitions was repeated with probes in different locations. High-order field dynamics were computed from this calibration probe data assembled from all scans, from which compression matrices could be devised using principal component analysis. Compression matrices were then utilized 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 for the calibration data. Results: Qualitative and quantitative improvements in accuracy were observed when using the proposed fitting method in comparison to the conventional approach. However, compression effectiveness was influenced by the specific acquisition data included in the calibration set. Conclusion: 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.