ReviewJournal of magnetic resonance imaging : JMRI2017
Compressed sensing for body MRI.
Review in Journal of magnetic resonance imaging : JMRI, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 131 papers.
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Who cites it
131 citing papers in PubMed.
- Parallelized 61-Sample Inhibition Screening Accelerated bySmall methods · 2026Article
- Deep learning reconstruction enables accelerated T2-weighted MRI for rectal cancer staging: a prospective study of diagnostic consistency across NEX value reduction.Abdominal radiology (New York) · 2026Article
- Intraindividual comparison of 3-T and 5-T gadoxetic acid-enhanced MRI for evaluating HCC: initial findings.Abdominal radiology (New York) · 2026Article
- Deep Learning-Augmented Zero Echo Time MRI Increases Diagnostic Confidence for Osseous Assessment in Hand and Foot MRI Protocols.Diagnostics (Basel, Switzerland) · 2026Article
- Deep learning-based high-resolution united compressed sensing for gadoxetic acid-enhanced liver magnetic resonance imaging in the detection of colorectal liver metastases.Quantitative imaging in medicine and surgery · 2026Article
- Hybrid learning: a combination of self-supervised and supervised learning for joint MRI reconstruction and denoising in low-field MRI.Physics in medicine and biology · 2026Article
- Improvement in Image Quality and Efficiency of Non-contrast Thoracic MR Angiography: Comparison of a Highly Accelerated Dixon-based Technique with the Conventional Fat-suppressed Technique.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026Article
- Self-Supervised Joint Reconstruction and Denoising of T2-Weighted PROPELLER MRI of the Lung at 0.55T.Magnetic resonance in medicine · 2026Article
- Accelerating CEST MRI through complementary undersampling and multi-offset transformer reconstruction.Communications engineering · 2026Article
- Accelerated magnetic resonance imaging of hippocampal sclerosis in pediatric patients with deep learning-based reconstruction: comparison of image quality and diagnostic performance with conventional reconstruction.Pediatric radiology · 2026Article
- Comparative evaluation of four reconstruction techniques for prostate T2-weighted MRI: Sensitivity encoding, compressed sensing, deep learning, and super-resolution.European journal of radiology open · 2025Article
- Pediatric Thoracic MRI: Safer, Sharper and Smarter Diagnostics.Children (Basel, Switzerland) · 2025Review
- High-acceleration pancreatobiliary MRI with deep learning-based super-resolution reconstruction for evaluating presumed pancreatic intraductal papillary mucinous neoplasm.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Deep learning and conventional hip MRI for the detection of labral and cartilage abnormalities using arthroscopy as standard of reference.European radiology · 2025Article
- Optimizing bladder magnetic resonance imaging: accelerating scan time and improving image quality through deep learning.Abdominal radiology (New York) · 2025Article
- Fast 3D wheel acquisition versus conventional parallel imaging in cerebral magnetic resonance angiography for the evaluation of intracranial aneurysms : Original Article.Neuroradiology · 2025Article
- Hemodynamic Characterization of Peripheral Arterio-Venous Malformations Using Rapid Contrast-Enhanced MR Imaging: An In Vitro and In Vivo Study.Annals of biomedical engineering · 2025Article
- Accelerated Abdominal MRI: A Review of Current Methods and Applications.Journal of magnetic resonance imaging : JMRI · 2025Review
- 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
- Effect of the Relationship between Respiratory Interval and Temporal Resolution on Image Quality in Free-breathing Abdominal MR Imaging.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Article
71 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
The introduction of compressed sensing for increasing imaging speed in magnetic resonance imaging (MRI) has raised significant interest among researchers and clinicians, and has initiated a large body of research across multiple clinical applications over the last decade. Compressed sensing aims to reconstruct unaliased images from fewer measurements than are traditionally required in MRI by exploiting image compressibility or sparsity. Moreover, appropriate combinations of compressed sensing with previously introduced fast imaging approaches, such as parallel imaging, have demonstrated further improved performance. The advent of compressed sensing marks the prelude to a new era of rapid MRI, where the focus of data acquisition has changed from sampling based on the nominal number of voxels and/or frames to sampling based on the desired information content. This article presents a brief overview of the application of compressed sensing techniques in body MRI, where imaging speed is crucial due to the presence of respiratory motion along with stringent constraints on spatial and temporal resolution. The first section provides an overview of the basic compressed sensing methodology, including the notion of sparsity, incoherence, and nonlinear reconstruction. The second section reviews state-of-the-art compressed sensing techniques that have been demonstrated for various clinical body MRI applications. In the final section, the article discusses current challenges and future opportunities. LEVEL OF EVIDENCE: 5 J. Magn. Reson. Imaging 2017;45:966-987.
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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.