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Published on: November 23, 2019
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Projection-based 3D/2D registration for prospective motion correction
Enrico Avventi1,2, Henric Ryden1,2, Ola Norbeck1,2
1Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden.
Magnetic Resonance in Medicine
|March 11, 2020
Summary
A new registration method estimates head motion using collapsed FatNav images. This technique effectively corrects motion artifacts, improving MRI image quality compared to existing retrospective methods.
Area of Science:
- Medical Imaging
- Magnetic Resonance Imaging (MRI)
- Image Registration
Background:
- Motion artifacts significantly degrade MRI quality, necessitating robust correction techniques.
- Prospective motion correction using navigators offers real-time artifact reduction.
- The collapsed FatNav is a navigator designed for short acquisition times and broad sequence compatibility.
Purpose of the Study:
- To develop and evaluate a 3D/2D registration method for estimating rigid body motion from collapsed FatNav images.
- To assess the accuracy and robustness of the proposed registration method.
- To compare prospective motion correction using the developed method with retrospective correction techniques.
Main Methods:
- A projection-based 3D/2D registration algorithm was adapted for collapsed FatNav data.
- Simulations using water/fat separated volumes evaluated accuracy at various resolutions.
- Prospective experiments in a healthy volunteer were conducted, comparing with PROPELLER retrospective correction.
Main Results:
- The proposed registration method demonstrated performance comparable to high-resolution 3D registration in simulations.
- The method showed robustness against different masking strategies and initial motion parameters.
- Prospective correction with collapsed FatNav successfully reduced motion artifacts and improved image quality over retrospective correction.
Conclusions:
- The 3D/2D registration method combined with collapsed FatNav offers an effective balance of speed and accuracy for motion estimation.
- This approach shows promise for prospective motion correction in MRI.
- Further validation across diverse anatomies is recommended.
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