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Artificial Intelligence and Deep Learning in Musculoskeletal Magnetic Resonance Imaging

DC Field Value Language
dc.contributor.author김성준-
dc.contributor.author송호택-
dc.contributor.author이영한-
dc.contributor.author이주희-
dc.date.accessioned2023-10-19T05:56:04Z-
dc.date.available2023-10-19T05:56:04Z-
dc.date.issued2023-06-
dc.identifier.issn2384-1095-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/196304-
dc.description.abstractThe application of artificial intelligence (AI) and deep learning (DL) in radiology is rapidly evolving. AI in healthcare has benefits for image recognition, classification, and radiological workflows from a clinical perspective. Additionally, clinical triage AI can be applied to triage systems. This review aims to introduce the concept of DL and discuss its applications in the interpretation of magnetic resonance (MR) images and the DL-based reconstruction of accelerated MR images, with an emphasis on musculoskeletal radiology. The most recent developments and future directions are also discussed briefly.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherKorean Society of Magnetic Resonance in Medicine-
dc.relation.isPartOfInvestigative Magnetic Resonance Imaging-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleArtificial Intelligence and Deep Learning in Musculoskeletal Magnetic Resonance Imaging-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Radiology (영상의학교실)-
dc.contributor.googleauthorSeung Dae Baek-
dc.contributor.googleauthorJoohee Lee-
dc.contributor.googleauthorSungjun Kim-
dc.contributor.googleauthorHo-Taek Song-
dc.contributor.googleauthorYoung Han Lee-
dc.identifier.doi10.13104/imri.2022.1102-
dc.contributor.localIdA00585-
dc.contributor.localIdA02080-
dc.contributor.localIdA02967-
dc.contributor.localIdA04786-
dc.relation.journalcodeJ01186-
dc.identifier.eissn2384-1109-
dc.subject.keywordArtificial intelligence-
dc.subject.keywordDeep learning-
dc.subject.keywordMusculoskeletal-
dc.subject.keywordMagnetic resonance imaging-
dc.contributor.alternativeNameKim, Sungjun-
dc.contributor.affiliatedAuthor김성준-
dc.contributor.affiliatedAuthor송호택-
dc.contributor.affiliatedAuthor이영한-
dc.contributor.affiliatedAuthor이주희-
dc.citation.volume27-
dc.citation.number2-
dc.citation.startPage67-
dc.citation.endPage74-
dc.identifier.bibliographicCitationInvestigative Magnetic Resonance Imaging, Vol.27(2) : 67-74, 2023-06-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers

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