Evidence map›Paper›PMID 37332879›Full record

ArticleFrontiers in neuroscience2023

Evaluation of kernel low-rank compressed sensing in preclinical diffusion magnetic resonance imaging.

Diego Alves Rodrigues de Souza, Hervé Mathieu, Jean-Christophe Deloulme, Emmanuel L Barbier

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Diego Alves Rodrigues de SouzaUniversité Grenoble Alpes, INSERM, U1216, Grenoble Institut Neurosciences, Grenoble, France.
Hervé MathieuUniversité Grenoble Alpes, INSERM, U1216, Grenoble Institut Neurosciences, Grenoble, France.
Jean-Christophe Deloulme *Université Grenoble Alpes, INSERM, U1216, Grenoble Institut Neurosciences, Grenoble, France.
Emmanuel L Barbier *Université Grenoble Alpes, INSERM, U1216, Grenoble Institut Neurosciences, Grenoble, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Compressed sensing (CS) is widely used to accelerate clinical diffusion MRI acquisitions, but it is not widely used in preclinical settings yet. In this study, we optimized and compared several CS reconstruction methods for diffusion imaging. Different undersampling patterns and two reconstruction approaches were evaluated: conventional CS, based on Berkeley Advanced Reconstruction Toolbox (BART-CS) toolbox, and a new kernel low-rank (KLR)-CS, based on kernel principal component analysis and low-resolution-phase (LRP) maps. 3D CS acquisitions were performed at 9.4T using a 4-element cryocoil on mice (wild type and a

Indexed as

Berkeley Advanced Reconstruction Toolbox (BART)composite real PCAcompressed sensing (CS)diffusion MRIkernel principal component analysismicrotubule-associated proteinmouse braintractography

Identifiers

PMID37332879
PMCPMC10272537

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Registered trials

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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.