Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling.

ABSTRACT:

Purpose

This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF).

Theory and methods

A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T₁ , T₂ , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dic

SUBMITTER: Zhao B 

PROVIDER: S-EPMC5641478 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature