MR-Compass: Inertial Navigation-Driven Motion Correction for Brain MRI

TL;DR

MR-Compass introduces a novel MRI motion correction method that uses inertial sensors and MRI data to accurately estimate head motion at high frequency, significantly improving image quality in brain scans.

Contribution

The paper presents a new inertial sensor-based approach that estimates 3-DOF orientation directly from MRI fields, eliminating drift and enabling high-rate motion correction.

Findings

Achieved mean orientation accuracy of 0.6° and 0.4 pixels in experiments.

Improved image quality in volunteer scans with retrospective and prospective correction.

Effective high-frequency head motion measurement during MRI scans.

Abstract

Inertial sensors can track object kinematics, however, unbounded drift from integrating noisy signals makes them impractical for MRI motion correction at millimeter resolution and minute-long scans. We introduce MR-Compass, which exploits the MRI system's static magnetic and gravitational fields to estimate 3-DOF orientation at 2 kHz directly, without integration, eliminating random-walk. The remaining 3-DOF translation is recovered via phase correlation from the MRI data. We experimentally validate the efficacy of the method retrospectively using a 3D radial koosh-ball sequence and prospectively using 2D EPI fMRI during large volunteer motions. MR-Compass followed by phase-correlation achieved a mean accuracy of 0.6$^o$ and 0.4 pixels across all experiments. Image quality improved when motion correction was applied in all volunteer scans for both retrospective and prospective correction cases. MR-Compass was effective in measuring head motion in the MRI scanner with high accuracy at unprecedented sample rates, and enabled both retrospective and prospective reconstruction to improve image quality by aligning the k-space data appropriately and by reducing the motion related artifacts.