Multimedia intelligent 3D images for automatic detection of sports injuries

被引：0
作者：
Liu H. [1 ]
机构：
[1] College of Physical Education, Baicheng Normal University, Jilin, Baicheng
来源：
Applied Mathematics and Nonlinear Sciences | 2024年 / 9卷 / 01期
关键词：
Image feature fusion; Intelligent 3D images; Multimedia; Sports injuries; Weight sharing network;
D O I：
10.2478/amns.2023.2.00882
中图分类号：
学科分类号：
摘要：
This paper uses the types and causes of sports injuries as the entry point to fuse 2D dynamic MRI with a 3D static motion for image alignment in multimedia 3D image plane technology. Using a weight-sharing network and convolution operation, sports injury features are extracted and fused, and a fusion detection framework for sports injury image features is created. Data analysis was conducted using an example to verify the detection framework's effectiveness. The results show that the peak signal-to-noise ratio of acquiring athletes' sports injury region imaging by the algorithm in this paper is 43 dB, and the average detection time is 5.91 s. The error control for sports injury detection was reduced from 0.102 to 0.011 after 600 iterations of the algorithm in this paper. © 2024 Applied Mathematics and Nonlinear Sciences. All rights reserved.
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