Real-time brain masking algorithm improves motion tracking accuracy in scans with volumetric navigators (vNavs).

Area of Science:

• Medical Imaging
• Neuroimaging
• Biomedical Engineering

Background:

• VNav-based detection is crucial for monitoring brain motion during MRI scans.
• Non-rigid anatomical deformations can introduce significant artifacts in motion detection.
• Existing methods may be susceptible to motion-related artifacts, impacting diagnostic accuracy.

Purpose of the Study:

• To investigate the impact of non-rigid deformations on vNav-based brain motion detection.
• To develop and evaluate a real-time brain extraction technique for vNavs.
• To demonstrate the efficacy of brain-masked registration in artifact removal.

Main Methods:

• Demonstration of artifact introduction due to non-rigid deformations (e.g., mouth movement).
• Development and implementation of a real-time brain extraction algorithm for vNav data.
• Application of brain-masked registration to processed vNav data.

Main Results:

• Non-rigid deformations were shown to introduce bias and artifacts in vNav-based brain motion detection.
• The real-time brain extraction method successfully isolated brain regions in vNavs.
• Brain-masked registration effectively removed the artifacts caused by non-rigid motion.

Conclusions:

• Non-rigid anatomical motion is a significant source of artifact in vNav-based brain motion detection.
• Real-time brain extraction is a viable method for improving vNav data quality.
• Brain-masked registration offers a robust solution for mitigating motion artifacts in neuroimaging.