General Phase Regularized Reconstruction using Phase Cycling

TL;DR

This paper introduces a general phase regularized reconstruction method with phase cycling, improving robustness and enabling joint imaging applications without phase unwrapping, applicable to various MRI techniques.

Contribution

A novel phase cycling technique that makes phase regularized reconstruction invariant to phase wraps and robust to initial solutions, applicable across multiple MRI imaging modalities.

Findings

Reduced artifacts with phase cycling compared to non-cycled methods

Achieved performance comparable to state-of-the-art in multiple imaging tasks

Demonstrated joint reconstruction of multiple imaging modalities

Abstract

Purpose: To develop a general phase regularized image reconstruction method, with applications to partial Fourier imaging, water-fat imaging and flow imaging. Theory and Methods: The problem of enforcing phase constraints in reconstruction was studied under a regularized inverse problem framework. A general phase regularized reconstruction algorithm was proposed to enable various joint reconstruction of partial Fourier imaging, water-fat imaging and flow imaging, along with parallel imaging (PI) and compressed sensing (CS). Since phase regularized reconstruction is inherently non-convex and sensitive to phase wraps in the initial solution, a reconstruction technique, named phase cycling, was proposed to render the overall algorithm invariant to phase wraps. The proposed method was applied to retrospectively under-sampled in vivo datasets and compared with state of the art reconstruction methods. Results: Phase cycling reconstructions showed reduction of artifacts compared to reconstructions with- out phase cycling and achieved similar performances as state of the art results in partial Fourier, water-fat and divergence-free regularized flow reconstruction. Joint reconstruction of partial Fourier + water-fat imaging + PI + CS, and partial Fourier + divergence-free regularized flow imaging + PI + CS were demonstrated. Conclusion: The proposed phase cycling reconstruction provides an alternative way to perform phase regularized reconstruction, without the need to perform phase unwrapping. It is robust to the choice of initial solutions and encourages the joint reconstruction of phase imaging applications.