Artificial intelligence powered advancements in upper extremity joint MRI: A review
文献类型：期刊论文
| 作者 | Chen, Wei1; Lim, Lincoln Jian Rong2,3; Lim, Rebecca Qian Ru4; Yi, Zhe1; Huang, Jiaxing5,6; He, Jia5,6; Yang, Ge5,6 ; Liu, Bo1
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| 刊名 | HELIYON
 |
| 出版日期 | 2024-04-15 |
| 卷号 | 10期号:7页码:13 |
| 关键词 | Artificial intelligence Deep learning Convolution neural network Upper extremity Magnetic resonance imaging |
| DOI | 10.1016/j.heliyon.2024.e28731 |
| 通讯作者 | Liu, Bo(drbobo7@sina.com) |
| 英文摘要 | Magnetic resonance imaging (MRI) is an indispensable medical imaging examination technique in musculoskeletal medicine. Modern MRI techniques achieve superior high-quality multiplanar imaging of soft tissue and skeletal pathologies without the harmful effects of ionizing radiation. Some current limitations of MRI include long acquisition times, artifacts, and noise. In addition, it is often challenging to distinguish abutting or closely applied soft tissue structures with similar signal characteristics. In the past decade, Artificial Intelligence (AI) has been widely employed in musculoskeletal MRI to help reduce the image acquisition time and improve image quality. Apart from being able to reduce medical costs, AI can assist clinicians in diagnosing diseases more accurately. This will effectively help formulate appropriate treatment plans and ultimately improve patient care. This review article intends to summarize AI's current research and application in musculoskeletal MRI, particularly the advancement of DL in identifying the structure and lesions of upper extremity joints in MRI images. |
| WOS关键词 | ROTATOR CUFF TEARS ; FATTY INFILTRATION ; SEGMENTATION ; SUPRASPINATUS ; ATROPHY ; WRIST ; RESOLUTION ; NETWORK ; IMPROVE ; MODELS |
| 资助项目 | National Natural Science Foundation of China[82272581] ; Beijing Hospitals Authority YangFan 3.0 Medical -Engineering Integration Cultivation Project[YGLX202314] ; Yunnan Provincial Science and Technology Talents and Platform Project[202105AF150050] ; Beijing Hospitals Authority's Ascent Plan[DFL20240402] |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:001217788100001 |
| 出版者 | CELL PRESS |
| 资助机构 | National Natural Science Foundation of China ; Beijing Hospitals Authority YangFan 3.0 Medical -Engineering Integration Cultivation Project ; Yunnan Provincial Science and Technology Talents and Platform Project ; Beijing Hospitals Authority's Ascent Plan |
| 源URL | [http://ir.ia.ac.cn/handle/173211/58404]  |
| 专题 | 模式识别国家重点实验室_计算生物学与机器智能 |
| 通讯作者 | Liu, Bo |
| 作者单位 | 1.Capital Med Univ, Beijing Jishuitan Hosp, Dept Hand Surg, 31 Xinjiekou East St, Beijing, Peoples R China 2.Footscray Hosp, Dept Med Imaging, Western Hlth, Footscray, Vic, Australia 3.Univ Melbourne, Dept Surg, Melbourne, Vic, Australia 4.Singapore Gen Hosp, Dept Hand & Reconstruct Microsurg, Singapore, Singapore 5.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 6.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Wei,Lim, Lincoln Jian Rong,Lim, Rebecca Qian Ru,et al. Artificial intelligence powered advancements in upper extremity joint MRI: A review[J]. HELIYON,2024,10(7):13. |
| APA | Chen, Wei.,Lim, Lincoln Jian Rong.,Lim, Rebecca Qian Ru.,Yi, Zhe.,Huang, Jiaxing.,...&Liu, Bo.(2024).Artificial intelligence powered advancements in upper extremity joint MRI: A review.HELIYON,10(7),13. |
| MLA | Chen, Wei,et al."Artificial intelligence powered advancements in upper extremity joint MRI: A review".HELIYON 10.7(2024):13. |
入库方式： OAI收割
来源：自动化研究所
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