A general algorithm for compensation of trajectory errors: Application to radial imaging.

Area of Science:

• Medical Imaging
• Magnetic Resonance Imaging (MRI)
• Signal Processing

Background:

• Gradient imperfections in MRI scanners cause trajectory errors, leading to phase inconsistencies and artifacts in fast scanning sequences.
• These artifacts degrade image quality and complicate diagnosis, necessitating robust correction methods.

Purpose of the Study:

• To develop and validate a novel algorithm for reconstructing artifact-free Magnetic Resonance Imaging (MRI) images from k-space data affected by trajectory deviations.
• To compensate for phase distortions caused by gradient imperfections without requiring explicit trajectory or phase calibration.

Main Methods:

• A novel framework utilizing a multi-block Hankel matrix is proposed, where each block corresponds to k-space segments with similar phase distortions.
• The reconstruction is formulated as a structured low-rank matrix optimization problem, leveraging the low-rank property of the block-Hankel matrix under smooth phase distortions.
• Coil sensitivities are assumed to be known for the reconstruction from partially parallel measurements.

Main Results:

• The algorithm was successfully tested on radial acquisitions, including partial Fourier and golden-angle acquisitions.
• Experiments demonstrated effective removal of artifacts caused by trajectory errors, achieving reconstruction quality comparable to existing methods like Trajectory Auto-Corrected Image Reconstruction (TrACR).
• The method successfully removed artifacts without requiring trajectory or phase calibration.

Conclusions:

• The proposed method offers a general and effective framework for recovering artifact-free images from radial trajectories.
• It eliminates the need for complex trajectory calibration, simplifying the MRI post-processing workflow.