Space-time variant weighted regularization in compressed sensing cardiac cine MRI

Publication date: Available online 14 January 2019

Source: Magnetic Resonance Imaging

Author(s): Alejandro Godino-Moya, Javier Royuela-del-Val, Muhammad Usman, Rosa-María Menchón-Lara, Marcos Martín-Fernández, Claudia Prieto, Carlos Alberola-López

Abstract

Purpose

To analyze the impact on image quality and motion fidelity of a motion-weighted space-time variant regularization term in compressed sensing cardiac cine MRI.

Methods

k-t SPARSE-SENSE with temporal total variation (tTV) is used as the base reconstruction algorithm. Motion in the dynamic image is estimated by means of a robust registration technique for non-rigid motion. The resulting deformation fields are used to leverage the regularization term. The results are compared with standard k-t SPARSE-SENSE with tTV regularization as well as with an improved version of this algorithm that makes use of tTV and temporal Fast Fourier Transform regularization in x-f domain.

Results

The proposed method with space-time variant regularization provides higher motion fidelity and image quality than the two previously reported methods. Difference images between undersampled reconstruction and fully sampled reference images show less systematic errors with the proposed approach.

Conclusions

Usage of a space-time variant regularization offers reconstructions with better image quality than the state of the art approaches used for comparison.

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