Simple auto-calibrated gradient delay estimation from few spokes using Radial Intersections (RING).

Area of Science:

• Magnetic Resonance Imaging (MRI)
• Image Reconstruction
• Signal Processing

Background:

• Gradient delays in radial MRI cause trajectory shifts, impacting image quality.
• Accurate estimation of these delays is crucial for correcting undersampled k-space data.

Purpose of the Study:

• To develop a simple and robust tool for estimating gradient delays.
• To enable accurate correction of gradient delays in highly undersampled radial k-space data.

Main Methods:

• Developed the Radial Imaging k-space Navigator (RING) method.
• Utilized an ellipse model to describe trajectory shifts caused by gradient delays.
• Employed a least-squares fit on spoke intersection points for parameter estimation.
• Validated RING using numerical simulations, phantom, and in vivo heart measurements.

Main Results:

• RING accurately estimates gradient delays.
• Robust performance was observed even with as few as three radial spokes.
• Comparison with correlation-based methods demonstrated RING's effectiveness.

Conclusions:

• The RING method offers a simple and straightforward approach for gradient delay estimation.
• Accurate gradient delay estimation is achievable for highly undersampled radial imaging.
• This method enhances the quality and reliability of radial MRI reconstructions.