Inertial Navigation Assisted Motion Correction for Brain MRI

PURPOSE: To assess the utility of inertial sensors for estimating parameters describing rigid body motion of the head, and to reduce motion related artifact through a hybrid prospective steering of the rotation via the sensor and retrospective realignment of translation via the MRI data. THEORY AND METHODS: and gravity are approximately orthogonal and can be exploited as reference vectors for 3-DOF orientation estimation. We introduce a hybrid inertial measurement-based method, which uses these fields to estimate 3-DOF orientation directly, without integration, thereby eliminating random walk. The remaining 3-DOF translation is recovered via phase correlation from the MRI data. We validate the efficacy of this hybrid method retrospectively using a 3D radial koosh-ball sequence and prospectively using 2D EPI time-series acquisition during volunteer motions. RESULTS: IMU-based orientation estimation followed by phase correlation achieved a mean accuracy of 0.6° 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. CONCLUSION: The proposed method measured head motion in the MRI scanner with high accuracy at unprecedented sampling rates and enabled both retrospective and prospective correction, improving image quality by aligning k-space data and reducing motion artifacts.