ArticleFrontiers in medicine2024
Feasibility of knee magnetic resonance imaging protocol using artificial intelligence-assisted iterative algorithm protocols: comparison with standard MRI protocols.
Article in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Feasibility of artificial intelligence-assisted fast magnetic resonance imaging technology in the ankle joint injury: a comparison of the proton density-weighted image.Frontiers in radiology · 2025Article
- Comments on "Detection of cholesteatoma recurrence by magnetic resonance imaging (DWI non-EPI sequence) - how can we minimise false results?"Polish journal of radiology · 2025Article
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Authors and funding
8 authors.
Funding
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Abstract
Objective: To evaluate the image quality and diagnostic performance of AI-assisted iterative algorithm protocols (AIIA) in accelerated fast spin-echo magnetic resonance imaging (MRI) versus standard (SD) fast spin-echo MRI for clinical 3.0 T rapid knee scans. Materials and methods: The accelerated sequence, which includes fat-suppression proton density-weighted imaging (FS-PDWI), T2-weighted imaging (T2WI), and T1-weighted imaging (T1WI), was used in conjunction with the SD sequence in 61 patients who underwent MRI scans. SD images were processed using standard reconstruction techniques, while accelerated images utilized AIIA reconstruction. Quantitative assessments of image quality were conducted, measuring noise levels, signal-to-noise ratio (SNR) and contrast signal-to-noise ratio (CNR). Additionally, subjective evaluations were performed using a Likert five-point scale to assess image quality. Results: The SD group completed the entire knee scan in 466 s, while the AIIA group completed the scan in 312 s. Compared to the SD group, the AIIA group had a noticeably higher SNR of T1WI in the femur and subpatellar fat pad ( Conclusion: Images processed using AIIA reconstruction were acquired faster while maintaining comparable image quality and diagnostic capability, meeting the requirements for clinical diagnosis.
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