ArticleMagnetic resonance in medicine2017
Compartmentalized low-rank recovery for high-resolution lipid unsuppressed MRSI.
Article in Magnetic resonance in medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- WALINET: A water and lipid identification convolutional neural network for nuisance signal removal inMagnetic resonance in medicine · 2025Article
- Dynamic Imaging Using Deep Bi-Linear Unsupervised Representation (DEBLUR).IEEE transactions on medical imaging · 2022Article
- Method for fast lipid reconstruction and removal processing inMagnetic resonance in medicine · 2021Article
- Achieving high-resolutionJournal of magnetic resonance (San Diego, Calif. : 1997) · 2021Article
- Accelerated radial echo-planar spectroscopic imaging using golden angle view-ordering and compressed-sensing reconstruction with total variation regularization.Magnetic resonance in medicine · 2021Article
- Accelerated MR spectroscopic imaging-a review of current and emerging techniques.NMR in biomedicine · 2021Review
- Ultrafast magnetic resonance spectroscopic imaging using SPICE with learned subspaces.Magnetic resonance in medicine · 2020Article
- Water removal in MR spectroscopic imaging with L2 regularization.Magnetic resonance in medicine · 2019Article
- DENOISING AND DEINTERLEAVING OF EPSI DATA USING STRUCTURED LOW-RANK MATRIX RECOVERY.Proceedings. IEEE International Symposium on Biomedical Imaging · 2018Article
- A minimum-phase Shinnar-Le Roux spectral-spatial excitation RF pulse for simultaneous water and lipid suppression inMagnetic resonance imaging · 2018Article
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2 authors.
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Abstract
purposeTo 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.
methodsThe 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.
resultsThe comparisons of the scheme against dual-resolution reconstruction algorithm on numerical phantom and in vivo datasets demonstrate the ability of the scheme to provide higher spatial resolution and lower lipid leakage artifacts. The experiments demonstrate the ability of the scheme to recover the metabolite maps, from lipid unsuppressed datasets with echo time (TE) = 55 ms.
conclusionThe proposed reconstruction method and data acquisition strategy provide an efficient way to achieve high-resolution metabolite maps without lipid suppression. This algorithm would be beneficial for fast metabolic mapping and extension to multislice acquisitions. Magn Reson Med 78:1267-1280, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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