Compartmentalized low-rank recovery for high-resolution lipid unsuppressed MRSI.

ABSTRACT:

Purpose

To introduce a novel algorithm for the recovery of high-resolution magnetic resonance spectroscopic imaging (MRSI) data with minimal lipid leakage artifacts, from dual-density spiral acquisition.

Methods

The reconstruction of MRSI data from dual-density spiral data is formulated as a compartmental low-rank recovery problem. The MRSI dataset is modeled as the sum of metabolite and lipid signals, each of which is support limited to the brain and extracranial regions, respectively, in addition to being orthogonal to each other. The reconstruction problem is formulated as an optimization problem, which is solved using iterative reweighted nuclear norm minimization.

Results

The comparisons of the scheme against dual-resolution reconstruction algorithm on numerical

SUBMITTER: Bhattacharya I 

PROVIDER: S-EPMC5427002 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature