Iterative off-resonance and signal decay estimation and correction for multi-echo MRI

Area of Science:

• Medical Imaging
• Biophysics

Background:

• Magnetic resonance imaging (MRI) is susceptible to artifacts like blurring and distortion.
• These artifacts arise from signal dephasing due to magnetic field inhomogeneity and signal decay from transverse relaxation.
• Current artifact correction methods often require separate data collection for field and relaxation maps.

Purpose of the Study:

• To develop an improved method for correcting artifacts in MRI.
• To jointly estimate images, field maps, and relaxation maps from multi-echo acquisitions.
• To enhance the quality of MRI images and the accuracy of derived maps.

Main Methods:

• An extension of a gridding-based algorithm for off-resonance correction was developed to incorporate signal decay correction.
• This enhanced algorithm was integrated into a novel fixed-point iteration framework.
• The approach was validated using both simulations and in vivo experiments.

Main Results:

• The proposed method successfully improved both the quality of MRI images and the accuracy of field and relaxation maps.
• Simulations and in vivo experiments demonstrated the effectiveness of the joint estimation technique.
• The rapid convergence of the fixed-point iteration and efficient gridding-based correction were highlighted.

Conclusions:

• The developed fixed-point iteration with integrated artifact correction offers a promising solution for improving MRI quality.
• This approach enables simultaneous estimation of images and crucial physiological maps.
• The method's efficiency suggests practical applicability for reducing MRI scan artifacts and improving diagnostic accuracy.