ArticleEuropean radiology2023
Magnetic resonance shoulder imaging using deep learning-based algorithm.
Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- 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
- Comparison of Deep-Learning-Based Reconstruction of Knee MRI with Conventional Sequences in Patients with Knee Pain.Diagnostics (Basel, Switzerland) · 2026Article
- Temporal AI-assisted compressed sensing for high-resolution, motion-robust small-bowel MR enterography without antiperistaltic agents: a feasibility study.European radiology · 2026Article
- Clinical application of a full free-breathing cardiac MRI protocol: feasibility, efficiency, and diagnostic accuracy.Quantitative imaging in medicine and surgery · 2026Article
- Accelerated MRI in temporomandibular joints using AI-assisted compressed sensing technique: a feasibility study.European radiology · 2025Article
- Accelerating brain T2-weighted imaging using artificial intelligence-assisted compressed sensing combined with deep learning-based reconstruction: a feasibility study at 5.0T MRI.BMC medical imaging · 2025Article
- Enhancing Radiologist Productivity with Artificial Intelligence in Magnetic Resonance Imaging (MRI): A Narrative Review.Diagnostics (Basel, Switzerland) · 2025Review
- Optimizing hip MRI: enhancing image quality and elevating inter-observer consistency using deep learning-powered reconstruction.BMC medical imaging · 2025Article
- AI-Assisted Compressed Sensing Enables Faster Brain MRI for the Elderly: Image Quality and Diagnostic Equivalence with Conventional Imaging.International journal of general medicine · 2025Article
- Accelerating brain three-dimensional T2 fluid-attenuated inversion recovery using artificial intelligence-assisted compressed sensing: a comparison study with parallel imaging.Quantitative imaging in medicine and surgery · 2024Article
- Application of Artificial Intelligence in Shoulder Pathology.Diagnostics (Basel, Switzerland) · 2024Review
- Review
- Deep learning-based reconstruction enhances image quality and improves diagnosis in magnetic resonance imaging of the shoulder joint.Quantitative imaging in medicine and surgery · 2024Article
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Authors and funding
11 authors.
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Abstract
objectiveTo investigate the feasibility of deep learning-based MRI (DL-MRI) in its application in shoulder imaging and compare its performance with conventional MR imaging (non-DL-MRI).
methodsThis retrospective study was approved by the local ethics committee. Seventy consecutive patients who had been examined with both DL-MRI and non-DL-MRI were enrolled for the image quality and lesion diagnosis comparison. Another 400 patients had been examined only with DL-MRI. Their images' quality was assessed by 20 radiologists using a satisfaction survey. The Kendall W test was performed to assess interobserver agreement. The Wilcoxon test was performed to compare the image quality. For lesion diagnosis, the interobserver and interstudy agreement were evaluated by kappa analysis.
resultsThe scan time of DL-MRI (6 min 1 s) was nearly 50% decreased compared with that of non-DL-MRI (11 min 25 s). The image quality was higher in both PDWI (4.85 ± 0.31 for DL, and 4.73 ± 0.29 for non-DL) and T2WI (4.95 ± 0.2 for DL, and 4.74 ± 0.41 for non-DL) of DL-MRI. Good interobserver agreement was found for the image quality of all the MR sequences on both DL-MRI (Kendall W: 0.588~0.902) and non-DL-MRI (Kendall W: 0751~0.865). Both the SNRs and |CNR| were significantly higher in PDWI and T2WI of DL-MRI. High interobserver and interstudy agreements for the lesions in non-DL-MRI and DL-MRI (kappa value = 0.913 to 1.000) were observed. The results of the image quality satisfaction survey in 400 patients receiving DL-MRI in the shoulder obtained 5 scores among all the radiologists.
conclusionShoulder DL-MRI can greatly reduce the scan time, while improve imaging quality of PDWI and T2WI compared to non-DL-MRI. KEY POINTS: • Shoulder 2D DL-MRI can greatly reduce the whole scan time and improve imaging quality of both PDWI and T2WI compared to conventional parallel MRI. • Shoulder 2D DL-MRI could be a clinical routine with greatly improved work efficiency in the future.
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