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Self-calibrated trajectory estimation and signal correction method for robust radial imaging using GRAPPA operator
Anagha Deshmane1, Martin Blaimer2, Felix Breuer2
1Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
Magnetic Resonance in Medicine
|March 14, 2015
Summary
This study introduces a novel method to correct miscentered radial imaging data without extra scans. The technique improves image quality by reducing artifacts caused by gradient errors in radial imaging.
Area of Science:
- Medical Imaging
- Magnetic Resonance Imaging (MRI)
Background:
- Radial imaging is susceptible to gradient errors causing miscentered projections.
- These errors lead to image artifacts and compromise direct current (DC) navigation reliability.
Purpose of the Study:
- To develop a retrospective technique for estimating trajectory errors in miscentered radial data.
- To improve image reconstruction without additional acquisitions or hardware modifications.
Main Methods:
- Employs phase correction and iterative self-calibrated GRAPPA operator gridding (GROG) weights.
- A search algorithm optimizes projection shifts by maximizing the sum-of-squares DC signal estimate.
Main Results:
- Successfully restored image quality in phantom, head, and heart datasets.
- Reduced artifacts like streaks and signal voids, increasing DC signal and reducing variability.
Conclusions:
- Retrospective phase correction and iterative GROG effectively estimate trajectory errors in 2D radial acquisitions.
- This method enhances image reconstruction without extra data or sequence modifications.
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