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Artificial Intelligence and Deep Learning in Musculoskeletal Magnetic Resonance Imaging

Authors
 Seung Dae Baek  ;  Joohee Lee  ;  Sungjun Kim  ;  Ho-Taek Song  ;  Young Han Lee 
Citation
 Investigative Magnetic Resonance Imaging, Vol.27(2) : 67-74, 2023-06 
Journal Title
Investigative Magnetic Resonance Imaging
ISSN
 2384-1095 
Issue Date
2023-06
Keywords
Artificial intelligence ; Deep learning ; Musculoskeletal ; Magnetic resonance imaging
Abstract
The 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.
Files in This Item:
T202305063.pdf Download
DOI
10.13104/imri.2022.1102
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Kim, Sungjun(김성준) ORCID logo https://orcid.org/0000-0002-7876-7901
Song, Ho Taek(송호택) ORCID logo https://orcid.org/0000-0002-6655-2575
Lee, Young Han(이영한) ORCID logo https://orcid.org/0000-0002-5602-391X
Lee, Joohee(이주희) ORCID logo https://orcid.org/0000-0002-7721-8935
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/196304
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