Hybrid prospective and retrospective head motion correction to mitigate cross-calibration errors

Area of Science:

• Medical Imaging
• Magnetic Resonance Imaging (MRI)

Background:

• External motion tracking devices offer emerging solutions for head motion correction in MRI.
• Cross-calibration between external trackers and MRI scanners presents a significant practical challenge.

Purpose of the Study:

• To present hybrid prospective and retrospective methods for head motion correction in MRI.
• To evaluate the effectiveness of these methods in the presence of cross-calibration errors.

Main Methods:

• Developed two hybrid methods combining optical-based prospective motion correction with retrospective entropy-based autofocusing.
• Investigated the impact of cross-calibration errors on image quality.

Main Results:

• Hybrid correction significantly improved image quality even with cross-calibration errors.
• The need for high-quality calibration scans was substantially reduced.
• External prospective motion tracking became feasible with only crude cross-calibration approximations.

Conclusions:

• Hybrid prospective and retrospective motion correction offers a robust solution for MRI.
• This approach relaxes stringent calibration requirements, enhancing practical applicability.
• The motion tracking system also benefits the retrospective autofocusing component.