Deep Learning for Spine MRI: Reducing Time Not Quality

医学 梅德林 人工智能 医学物理学 核医学 计算机科学 政治学 法学
作者
James Thomas Patrick Decourcy Hallinan
出处
期刊:Radiology [Radiological Society of North America]
卷期号:306 (3)
标识
DOI:10.1148/radiol.222410
摘要

HomeRadiologyVol. 306, No. 3 PreviousNext Reviews and CommentaryEditorialDeep Learning for Spine MRI: Reducing Time Not QualityJames Thomas Patrick Decourcy Hallinan James Thomas Patrick Decourcy Hallinan Author AffiliationsFrom the Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074; and Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.Address correspondence to the author (email: [email protected]).James Thomas Patrick Decourcy Hallinan Published Online:Nov 1 2022https://doi.org/10.1148/radiol.222410MoreSectionsFull textPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In References1. Katz JN, Zimmerman ZE, Mass H, Makhni MC. Diagnosis and Management of Lumbar Spinal Stenosis: A Review. JAMA 2022;327(17):1688–1699. Crossref, Medline, Google Scholar2. Zeng G, Guo Y, Zhan J, et al. A review on deep learning MRI reconstruction without fully sampled k-space. BMC Med Imaging 2021;21(1):195. Crossref, Medline, Google Scholar3. Antun V, Renna F, Poon C, Adcock B, Hansen AC. On instabilities of deep learning in image reconstruction and the potential costs of AI. Proc Natl Acad Sci U S A 2020;117(48):30088–30095. Crossref, Medline, Google Scholar4. Almansour H, Herrmann J, Gassenmaier S, et al. Deep learning reconstruction for accelerated spine MRI: prospective analysis of interchangeability. Radiology 2023;306(3):e212922. https://doi.org/10.1148/radiol.212922. Published online November 1, 2022. Google Scholar5. Johnson PM, Recht MP, Knoll F. Improving the Speed of MRI with Artificial Intelligence. Semin Musculoskelet Radiol 2020;24(1):12–20. Crossref, Medline, Google Scholar6. Gassenmaier S, Afat S, Nickel D, Mostapha M, Herrmann J, Othman AE. Deep learning-accelerated T2-weighted imaging of the prostate: Reduction of acquisition time and improvement of image quality. Eur J Radiol 2021;137:109600. Crossref, Medline, Google Scholar7. Gassenmaier S, Afat S, Nickel MD, et al. Accelerated T2-Weighted TSE Imaging of the Prostate Using Deep Learning Image Reconstruction: A Prospective Comparison with Standard T2-Weighted TSE Imaging. Cancers (Basel) 2021;13(14):3593. Crossref, Medline, Google Scholar8. Herrmann J, Keller G, Gassenmaier S, et al. Feasibility of an accelerated 2D-multi-contrast knee MRI protocol using deep-learning image reconstruction: a prospective intraindividual comparison with a standard MRI protocol. Eur Radiol 2022;32(9):6215–6229. Crossref, Medline, Google Scholar9. Del Grande F, Rashidi A, Luna R, et al. Five-Minute Five-Sequence Knee MRI Using Combined Simultaneous Multislice and Parallel Imaging Acceleration: Comparison with 10-Minute Parallel Imaging Knee MRI. Radiology 2021;299(3):635–646. Link, Google Scholar10. Bash S, Johnson B, Gibbs W, Zhang T, Shankaranarayanan A, Tanenbaum LN. Deep Learning Image Processing Enables 40% Faster Spinal MR Scans Which Match or Exceed Quality of Standard of Care : A Prospective Multicenter Multireader Study. Clin Neuroradiol 2022;32(1):197–203. Crossref, Medline, Google ScholarArticle HistoryReceived: Sept 1 2022Revision requested: Sept 30 2022Revision received: Oct 1 2022Accepted: Oct 5 2022Published online: Nov 01 2022 FiguresReferencesRelatedDetailsAccompanying This ArticleDeep Learning Reconstruction for Accelerated Spine MRI: Prospective Analysis of InterchangeabilityNov 1 2022RadiologyRecommended Articles Deep Learning Reconstruction for Accelerated Spine MRI: Prospective Analysis of InterchangeabilityRadiology2022Volume: 306Issue: 3Establishing a New Normal: The 5-Minute MRIRadiology2021Volume: 299Issue: 3pp. 647-648Uncommon Manifestations of Intervertebral Disk Pathologic ConditionsRadioGraphics2016Volume: 36Issue: 3pp. 801-823Optimizing Diffusion-Tensor Imaging Acquisition for Spinal Cord Assessment: Physical Basis and Technical AdjustmentsRadioGraphics2020Volume: 40Issue: 2pp. 403-427Invited Commentary on “Optimizing Diffusion-Tensor Imaging Acquisition for Spinal Cord Assessment,” with Response from Dr Martín Noguerol et alRadioGraphics2020Volume: 40Issue: 2pp. 428-431See More RSNA Education Exhibits CT Myelography: From Technical Aspects to Imaging EvaluationDigital Posters2022Is Your Head Spinning Yet? MRI Acceleration Techniques for the MSK GuyDigital Posters2019Spinal Diffusion Weighted Imaging (DWI): From Ischemia to BacteremiaDigital Posters2020 RSNA Case Collection Early spine infectionRSNA Case Collection2022Spinal epidural abscess RSNA Case Collection2020Hirayama DiseaseRSNA Case Collection2021 Vol. 306, No. 3 Metrics Altmetric Score PDF download
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