Physics-based Reconstruction Methods for Magnetic Resonance Imaging

TL;DR

This paper reviews physics-based model-driven MRI reconstruction methods that improve scan times and enable direct extraction of quantitative parameters by formulating the process as an inverse problem.

Contribution

It provides a comprehensive overview of model-based MRI reconstruction techniques, including practical examples, data, and code developed over the past decade.

Findings

Model-based methods reduce scan times

Enable direct quantitative parameter extraction

Improved image quality and comparability

Abstract

Conventional Magnetic Resonance Imaging (MRI) is hampered by long scan times and only qualitative image contrasts that prohibit a direct comparison between different systems. To address these limitations, model-based reconstructions explicitly model the physical laws that govern the MRI signal generation. By formulating image reconstruction as an inverse problem, quantitative maps of the underlying physical parameters can then be extracted directly from efficiently acquired k-space signals without intermediate image reconstruction -- addressing both shortcomings of conventional MRI at the same time. This review will discuss basic concepts of model-based reconstructions and report about our experience in developing several model-based methods over the last decade using selected examples that are provided complete with data and code.