ArticleJournal of magnetic resonance imaging : JMRI2021
Performance Comparison of Compressed Sensing Algorithms for Accelerating T
Article in Journal of magnetic resonance imaging : JMRI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
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.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Fast 3D-MRSI using sparse acquisition and 4D compressed sensing reconstruction.Magma (New York, N.Y.) · 2026Article
- Grading of glioma and prediction of IDH mutation status via longitudinal relaxation time in rotating frame mapping on 5-T magnetic resonance imaging: added value to amide proton transfer-weighted imaging.Quantitative imaging in medicine and surgery · 2026Article
- Endogenous assessment of late gadolinium enhancement grey area in patients with chronic myocardial infarction using T1rho mapping.Quantitative imaging in medicine and surgery · 2025Article
- Data-driven optimization of sampling patterns for MR brain TMagnetic resonance in medicine · 2023Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
background3D-T PURPOSE: To compare the performance of five compressed sensing (CS) algorithms-spatiotemporal finite differences (STFD), exponential dictionary (EXP), 3D-wavelet transform (WAV), low-rank (LOW) and low-rank plus sparse model with spatial finite differences (L + S SFD)-for 3D-T STUDY TYPE: Retrospective. SUBJECTS: Eight healthy volunteers underwent T FIELD STRENGTH/SEQUENCE: The sequence was fully sampled 3D Cartesian ultrafast gradient echo sequence with a customized T ASSESSMENT: The fully sampled data was undersampled by factors of 2, 5, and 10 and reconstructed with the five CS algorithms. Image reconstruction quality was evaluated and compared to the SENSE reconstruction of the fully sampled data (reference) and T STATISTICAL TESTS: Normalized root mean squared errors (nRMSE) and median normalized absolute deviation (MNAD) errors were calculated to compare image reconstruction errors and T
resultsFor image reconstruction quality, at AF = 2, EXP transforms had the lowest mRMSE (1.56%). At higher AF values, STFD performed better, with the smallest errors (3.16% at AF = 5, 4.32% at AF = 10). For whole-brain quantitative T DATA
conclusionThis study demonstrates the use of different CS algorithms that may be useful in reducing the scan time required to perform volumetric T LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 1.
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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.