ArticleMagnetic resonance in medicine2013
Soft constraints in nonlinear spectral fitting with regularized lineshape deconvolution.
Article in Magnetic resonance in medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Effects of noise and linewidth on in vivo analysis of glutamate at 3 T.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2020Article
- Fitting interrelated datasets: metabolite diffusion and general lineshapes.Magma (New York, N.Y.) · 2017Article
- Simultaneous quantification of glutamate and glutamine by J-modulated spectroscopy at 3 Tesla.Magnetic resonance in medicine · 2016Article
- Regional and tissue-specific differences in brain glutamate concentration measured by in vivo single voxel MRS.Journal of neuroscience methods · 2015Article
- Smoothness of in vivo spectral baseline determined by mean-square error.Magnetic resonance in medicine · 2014Article
- Quantification in magnetic resonance spectroscopy based on semi-parametric approaches.Magma (New York, N.Y.) · 2014Review
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
Abstract
This article presents a novel method for incorporating a priori knowledge into regularized nonlinear spectral fitting as soft constraints. Regularization was recently introduced to lineshape deconvolution as a method for correcting spectral distortions. Here, the deconvoluted lineshape was described by a new type of lineshape model and applied to spectral fitting. The nonlinear spectral fitting was carried out in two steps that were subject to hard constraints and soft constraints, respectively. The hard constraints step provided a starting point and, therefore, only the changes of the relevant variables were constrained in the soft constraints step and incorporated into the linear substeps of the Levenberg-Marquardt algorithm. The method was demonstrated using localized averaged echo time point resolved spectroscopy proton spectroscopy of human brains.
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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.