Phase-Updated Regularized SENSE for Navigator-Free Multishot Diffusion Imaging

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Abstract

Purpose:

Either SENSE+CG or POCS-ICE methods can be used to correct for motion-induced phase errors in navigator-free multishot diffusion imaging. SENSE+CG has the advantage of a fast convergence, however, occasionally the convergence can be unstable, thus degrading the image quality. POCS-ICE has a stable convergence and can be used with a high number of shots, but its convergence is slow, which limits its practical usage. The study here proposes an improved method based on both SENSE+CG and POCS-ICE, called Phase-updated Regularized SENSE (PR-SENSE), for navigator-free multishot diffusion imaging.

Theory and Methods:

In PR-SENSE, a total variation regularization method is used to solve the SENSE inverse problem instead of the conjugate gradient method used in SENSE+CG. This method is implemented by using a lagged diffusivity fixed point iteration algorithm. Additionally, the phase is updated during the iteration process to improve the image accuracy.

Results:

Simulations and in vivo experiments demonstrated that PR-SENSE can successfully correct for the motion-induced phase errors in multi-shot DWI. It integrates the advantages of SENSE+CG and POCS-ICE, resulting in a fast and stable convergence with improved image quality.

Conclusion:

Given its advantages, PR-SENSE is a significant improvement over other methods for navigator-free high-resolution DWI.

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