Multicomponent MR fingerprinting reconstruction using joint-sparsity and low-rank constraints.

ABSTRACT:

Purpose

To develop an efficient algorithm for multicomponent MR fingerprinting (MC-MRF) reconstructions directly from highly undersampled data without making prior assumptions about tissue relaxation times and expected number of tissues.

Methods

The proposed method reconstructs MC-MRF maps from highly undersampled data by iteratively applying a joint-sparsity constraint to the estimated tissue components. Intermediate component maps are obtained by a low-rank multicomponent alternating direction method of multipliers (MC-ADMM) including the non-negativity of tissue weights as an extra regularization term. Over iterations, the used dictionary compression is adjusted. The proposed method (k-SPIJN) is compared with a two-step approach in which image reconstruction and multicomp

SUBMITTER: Nagtegaal M 

PROVIDER: S-EPMC9825911 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature