Fully Automatic Knee Joint Segmentation and Quantitative Analysis for Osteoarthritis from Magnetic Resonance (MR) Images Using a Deep Learning Model-Reference-Cited by-同舟云学术

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Fully Automatic Knee Joint Segmentation and Quantitative Analysis for Osteoarthritis from Magnetic Resonance (MR) Images Using a Deep Learning Model

Published:2022-05-23 Issue: Volume:28 Page:
ISSN:1643-3750
Container-title:Medical Science Monitor
language:en
Short-container-title:Med Sci Monit

Author:

Tang Xiongfeng¹,Guo Deming¹,Liu Aie²,Wu Dijia²,Liu Jianhua³,Xu Nannan³,Qin Yanguo⁴

Affiliation:

1. Orthpoeadic Medical Center, Jilin University Second Hospital, Changchun, Jilin, China (mainland)

2. Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China (mainland)

3. Department of Radiology, Second Hospital of Jilin University, Changchun, Jilin, China (mainland)

4. Orthopedic Medical Center, Jilin University Second Hospital, Changchun, Jilin, China (mainland)

Publisher

International Scientific Information, Inc.

Subject

General Medicine

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhanced Attention Res-Unet for Segmentation of Knee Bones;Mathematics;2024-07-22

2. The Role of Artificial Intelligence in Osteoarthritis;Seminars in Roentgenology;2024-07

3. Source-free unsupervised adaptive segmentation for knee joint MRI;Biomedical Signal Processing and Control;2024-06

4. Automated measurement and grading of knee cartilage thickness: a deep learning-based approach;Frontiers in Medicine;2024-02-29

5. Survival analysis on subchondral bone length for total knee replacement;Skeletal Radiology;2024-02-22

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