ArticleMagnetic resonance in medicine2017
High-resolution
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 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed.
- Exploring in vivo human brain metabolism at 10.5 T: Initial insights from MR spectroscopic imaging.NeuroImage · 2025Article
- Joint learning of nonlinear representation and projection for fast constrained MRSI reconstruction.Magnetic resonance in medicine · 2025Article
- Accelerated 3D metabolite TMagnetic resonance in medicine · 2024Article
- Simultaneous high-resolution whole-brain MR spectroscopy and [European journal of nuclear medicine and molecular imaging · 2024Article
- Joint spectral quantification of MR spectroscopic imaging using linear tangent space alignment-based manifold learning.Magnetic resonance in medicine · 2023Article
- High-resolution, 3D multi-TEMagnetic resonance in medicine · 2022Article
- Method for fast lipid reconstruction and removal processing inMagnetic resonance in medicine · 2021Article
- Accelerated MR spectroscopic imaging-a review of current and emerging techniques.NMR in biomedicine · 2021Review
- Advanced magnetic resonance spectroscopic neuroimaging: Experts' consensus recommendations.NMR in biomedicine · 2021Article
- Separation of Metabolites and Macromolecules for Short-TEIEEE transactions on medical imaging · 2021Article
- Fast Imaging for Hyperpolarized MR Metabolic Imaging.Journal of magnetic resonance imaging : JMRI · 2021Review
- Accelerated J-resolvedMagnetic resonance in medicine · 2021Article
- Lipid-suppressed and tissue-fraction corrected metabolic distributions in human central brain structures using 2DBrain and behavior · 2020Article
- Echo planar time-resolved imaging with subspace reconstruction and optimized spatiotemporal encoding.Magnetic resonance in medicine · 2020Article
- High-Resolution DynamicIEEE transactions on bio-medical engineering · 2020Article
- Terminology and concepts for the characterization of in vivo MR spectroscopy methods and MR spectra: Background and experts' consensus recommendations.NMR in biomedicine · 2020Article
- Ultrafast magnetic resonance spectroscopic imaging using SPICE with learned subspaces.Magnetic resonance in medicine · 2020Article
- Echo planar time-resolved imaging (EPTI).Magnetic resonance in medicine · 2019Article
- Miniature pig magnetic resonance spectroscopy model of normal adolescent brain development.Journal of neuroscience methods · 2018Article
- Pulse sequences and parallel imaging for high spatiotemporal resolution MRI at ultra-high field.NeuroImage · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
purposeTo improve signal-to-noise ratio (SNR) for high-resolution spectroscopic imaging using a subspace-based technique known as SPectroscopic Imaging by exploiting spatiospectral CorrElation (SPICE).
methodsThe proposed method is based on a union-of-subspaces model of MRSI signals, which exploits the partial separability properties of water, lipid, baseline and metabolite signals. Enabled by this model, a special scheme is used for accelerated data acquisition, which includes a double-echo CSI component used to collect a "training" dataset (for determination of the basis functions) and a short-TE EPSI component used to collect a sparse "imaging" dataset (for determination of the overall spatiospectral distributions). A set of signal processing algorithms are developed to remove the water and lipid signals and jointly reconstruct the metabolite and baseline signals.
resultsIn vivo
conclusionsThe proposed method can effectively remove nuisance signals and reconstruct high-resolution spatiospectral functions from sparse data to make short-TE SPICE possible. The method should prove useful for high-resolution
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.