ArticleRadiological physics and technology2018
Undersampling patterns in k-space for compressed sensing MRI using two-dimensional Cartesian sampling.
Article in Radiological physics and technology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Correlation of objective image quality metrics with radiologists' diagnostic confidence depends on the clinical task performed.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- Assessing deep learning reconstruction for faster prostate MRI: visual vs. diagnostic performance metrics.European radiology · 2024Article
- A novel automatic segmentation method directly based on magnetic resonance imaging K-space data for auxiliary diagnosis of glioma.Quantitative imaging in medicine and surgery · 2024Article
- Applications and implementation of generative artificial intelligence in cardiovascular imaging with a focus on ethical and legal considerations: what cardiovascular imagers need to know!BJR artificial intelligence · 2024Review
- Optimization of undersampling parameters for 3D intracranial compressed sensing MR angiography at 7 T.Magnetic resonance in medicine · 2022Article
- Noise power spectrum in compressed sensing magnetic resonance imaging.Radiological physics and technology · 2021Article
- Evaluation of Golden-Angle-Sampled Dynamic Contrast-Enhanced MRI Reconstruction Using Objective Image Quality Measures: A Simulated Phantom Study.Tomography (Ann Arbor, Mich.) · 2020Article
- Reduction of procedure times in routine clinical practice with Compressed SENSE magnetic resonance imaging technique.PloS one · 2019Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In compressed sensing magnetic resonance imaging (CS-MRI), undersampling of k-space is performed to achieve faster imaging. For this process, it is important to acquire data randomly, and an optimal random undersampling pattern is required. However, random undersampling is difficult in two-dimensional (2D) Cartesian sampling. In this study, the effect of random undersampling patterns on image reconstruction was clarified using phantom and in vivo MRI, and a sampling pattern relevant for 2D Cartesian sampling in CS-MRI is suggested. The precision of image restoration was estimated with various acceleration factors and extents for the fully sampled central region of k-space. The root-mean-square error, structural similarity index, and modulation transfer function were measured, and visual assessments were also performed. The undersampling pattern was shown to influence the precision of image restoration, and an optimal undersampling pattern should be used to improve image quality; therefore, we suggest that the ideal undersampling pattern in CS-MRI for 2D Cartesian sampling is one with a high extent for the fully sampled central region of k-space.
Indexed as
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Registered trials
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