The DOI matches its Crossref record.
Medical Sports Rehabilitation Deep Learning System of Sports Injury Based on MRI Image Analysis
Abstract
Medical sports rehabilitation deep learning system of sports injury based on MRI image analysis is proposed in this paper. Preparation activities are various body exercises that are purposely performed before physical education, training, and competition. It is a transitional phase from the static state to the moving state of the human body. Preparatory activities can improve the excitability of the central nervous system, improve the ability of the cerebral cortex to analyze and judge movements, and thus make the movement more coordinated and accurate. At the same time prepare activity can also improve the respiratory and circulatory system functions and reduce the muscles, ligaments of the sticky nature and the contraction of muscles for speed and strength, in order to maximize the capacity of the physical movement and injury prevention campaign ready. Therefore, how to use the MRI image to numerically analyze the mentioned task is essential. We integrate the deep learning model to propose the novel image enhancement and recognition model to undertake the task of medical sports rehabilitation system. The experimental result proves the performance is robust.
Overview
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Cited by
Analysis and design of dual-feature fusion neural network for sports injury estimation model
Meng, L., & Qiao, E. (2021) · Neural Computing and Applications · doi:10.1007/s00521-021-06151-y · Cited by 47
Luo, A., Gou, S., Tong, N., Liu, B., Jiao, L., Xu, H., Wang, Y. G., & Ding, T. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01082-z · Cited by 26
“To ensure appropriate treatment of meniscal injuries, precise grading methods based on knee MRI have been proposed to distinctly assess the injury severity 2 – 4 .”
Real-time sports injury monitoring system based on the deep learning algorithm
Ren, L., Wang, Y., & Li, K. (2024) · BMC Medical Imaging · doi:10.1186/s12880-024-01304-6 · Cited by 25
“Compared to existing methods that use similar data, such as MRI [21], the system proposed in this document offers greater real-time capability and specificity, allowing faster and more accurate injury analysis and risk warning, thus protecting the health of athletes.”
MethodCai, H. W. (2022) · The Journal of Supercomputing · doi:10.1007/s11227-021-04145-0 · Cited by 22
“Fitness activities encompass a diversified list of sports during which an effective and scientific training strategy is crucial, since improper training may lead to workout injuries, such as sprained ankles and muscle pulls and strain [1, 2].”
BackgroundMethodCui, H., & Chang, C. (2020) · IEEE Access · doi:10.1109/access.2020.3003652 · Cited by 19
“Today, digital technologies are introducing to the sports arena due to secure mobile networks, wearable, and artificial intelligence technology [1].”
Background
Metadata
- Authors
- Ba, H.
- Affiliations
- Aba Teachers University (CN)
- Corresponding author
- Ba, Hongbing
- Venue
- Journal of Medical Imaging and Health Informatics
- Publisher
- American Scientific Publishers
- Published
- 2020-05-01
- Volume
- 10
- Issue
- 5
- Pages
- 1091-1097
- ISSN
- 2156-7018 (ISSN-L)
- OpenAlex
- W3006109402
- Semantic Scholar
- 2ad6a37ee0163a79a6abda6e6ffbca6fb6b0f66f
- Cited by
- 30
- References
- 0
- Citations by year
- 2024: 8 · 2023: 2 · 2022: 10 · 2021: 8 · 2020: 2
- FWCI
- 4.96
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Medical Imaging and Health Informatics (publishedVersion)
- Topics
- Health Sciences › Medicine › Orthopedics and Sports Medicine › Sports injuries and prevention
- Physical Sciences › Engineering › Biomedical Engineering › Medical Imaging and Analysis
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- sports injuries, sports rehabilitation, MRI image analysis, deep learning, image enhancement, injury recognition, warm-up, injury prevention
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- This page
- CoChat. (2026). Citation check: Medical Sports Rehabilitation Deep Learning System of Sports Injury Based on MRI Image Analysis. https://app.cochat.ai/papers/10.1166/jmihi.2020.2892
- The paper
- Ba, H. (2020). Medical Sports Rehabilitation Deep Learning System of Sports Injury Based on MRI Image Analysis. Journal of Medical Imaging and Health Informatics. https://doi.org/10.1166/jmihi.2020.2892
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
