ReviewJournal of magnetic resonance imaging : JMRI2018
Rapid compositional mapping of knee cartilage with compressed sensing MRI.
Review in Journal of magnetic resonance imaging : JMRI, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Optimizing variable flip angles in magnetization-prepared gradient-echo sequences for efficient 3D-T1ρ mapping.Magnetic resonance in medicine · 2023Article
- Automated Parameter Selection for Accelerated MRI Reconstruction via Low-Rank Modeling of Local k-Space Neighborhoods.Zeitschrift fur medizinische Physik · 2023Article
- Review of Quantitative Knee Articular Cartilage MR Imaging.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2022Article
- Alternating Learning Approach for Variational Networks and Undersampling Pattern in Parallel MRI Applications.IEEE transactions on computational imaging · 2022Article
- Fast data-driven learning of parallel MRI sampling patterns for large scale problems.Scientific reports · 2021Article
- Feasibility and Implementation of a Deep Learning MR Reconstruction for TSE Sequences in Musculoskeletal Imaging.Diagnostics (Basel, Switzerland) · 2021Article
- Accelerating the 3D TQuantitative imaging in medicine and surgery · 2021Article
- Measurement of Three-Dimensional Internal Dynamic Strains in the Intervertebral Disc of the Lumbar Spine With Mechanical Loading and Golden-Angle Radial Sparse Parallel-Magnetic Resonance Imaging.Journal of magnetic resonance imaging : JMRI · 2021Review
- Accelerated T2 Mapping of the Lumbar Intervertebral Disc: Highly Undersampled K-Space Data for Robust T2 Relaxation Time Measurement in Clinically Feasible Acquisition Times.Investigative radiology · 2020Article
- In vivo tibiofemoral cartilage strain mapping under static mechanical loading using continuous GRASP-MRI.Journal of magnetic resonance imaging : JMRI · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
More than a decade after the introduction of compressed sensing (CS) in MRI, researchers are still working on ways to translate it into different research and clinical applications. The greatest advantage of CS in MRI is the reduced amount of k-space data needed to reconstruct images, which can be exploited to reduce scan time or to improve spatial resolution and volumetric coverage. Efficient data acquisition using CS is extremely important for compositional mapping of the musculoskeletal system in general and knee cartilage mapping techniques in particular. High-resolution quantitative information about tissue biochemical composition could be obtained in just a few minutes using CS MRI. However, in order to make this goal a reality, some issues still need to be addressed. In this article we review the current state of the art of CS methods for rapid compositional mapping of knee cartilage. Specifically, data acquisition strategies, image reconstruction algorithms, and data fitting models are discussed. Different CS studies for T
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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.