ReviewInvestigative radiology2016
Sparse Reconstruction Techniques in Magnetic Resonance Imaging: Methods, Applications, and Challenges to Clinical Adoption.
Review in Investigative radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
55 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI-accelerated prostate MRI: a systematic review.The British journal of radiology · 2024Pooled it
- New pulse sequence for improving cardiac black-blood and PSIR MRI quality in cases of arrhythmia.Magnetic resonance letters · 2027Article
- Intraindividual comparison of 3-T and 5-T gadoxetic acid-enhanced MRI for evaluating HCC: initial findings.Abdominal radiology (New York) · 2026Article
- Best fast MRI protocols for the knee: advantages and limitations.Skeletal radiology · 2026Review
- Listening Without the Noise: Near-Silent Looping Star fMRI Reveals Neural Processing of Degraded Speech.Human brain mapping · 2026Article
- Application of AI-assisted compressed sensing in high resolution Gd-EOB-DTPA-enhanced MRI during hepatobiliary phase at 5.0 T.Quantitative imaging in medicine and surgery · 2025Article
- AI-augmented reconstruction provides improved image quality and enables shorter breath-holds in contrast-enhanced liver MRI.European radiology experimental · 2025Article
- A method for quantifying and automatic grading of musculoskeletal ultrasound superb microvascular imaging based on dynamic analysis of optical flow model.Scientific reports · 2025Article
- Pulsation artifact reduction using compressed sensitivity encoding in Gd-EOB-DTPA contrast-enhanced magnetic resonance imaging.Radiological physics and technology · 2025Article
- Rapid and motion-robust pediatric brain imaging: T2-weighted turbo-spin-echo PROPELLER acquisition with compressed sensing.Pediatric radiology · 2025Article
- Fast 3D fMRI acquisition with high spatial resolutions over a reduced FOV.Magnetic resonance in medicine · 2024Article
- Comprehensive review of artifacts in cardiac MRI and their mitigation.The international journal of cardiovascular imaging · 2024Review
- Acceleration of uterine 3D T2-weighted imaging by compressed SENSE-a multicentre study.The British journal of radiology · 2024Article
- Modern acceleration in musculoskeletal MRI: applications, implications, and challenges.Skeletal radiology · 2024Review
- Compressed SENSitivity Encoding (SENSE): Qualitative and Quantitative Analysis.Diagnostics (Basel, Switzerland) · 2024Article
- Seeing between Time: Higher Frame Rate Cardiac Cine MRI using Deep Learning.Radiology. Cardiothoracic imaging · 2024Article
- Breath-hold High-resolution T1-weighted Gradient Echo Liver MR Imaging with Compressed Sensing Obtained during the Gadoxetic Acid-enhanced Hepatobiliary Phase: Image Quality and Lesion Visibility Compared with a Standard T1-weighted Sequence.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024Article
- Radiomic feature reliability of amide proton transfer-weighted MR images acquired with compressed sensing at 3T.International journal of imaging systems and technology · 2024Article
- Iterative Denoising Accelerated 3D FLAIR Sequence for Hydrops MR Imaging at 3T.AJNR. American journal of neuroradiology · 2023Article
- Brain morphometry in older adults with and without dementia using extremely rapid structural scans.NeuroImage · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in magnetic resonance imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstructions, they all rely on the idea that a priori information about the sparsity of MR images can be used to reconstruct full images from undersampled data. This review describes the basic ideas behind sparse reconstruction techniques, how they could be applied to improve MRI, and the open challenges to their general adoption in a clinical setting. The fundamental principles underlying different classes of sparse reconstructions techniques are examined, and the requirements that each make on the undersampled data outlined. Applications that could potentially benefit from the accelerations that sparse reconstructions could provide are described, and clinical studies using sparse reconstructions reviewed. Lastly, technical and clinical challenges to widespread implementation of sparse reconstruction techniques, including optimization, reconstruction times, artifact appearance, and comparison with current gold standards, are discussed.
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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.