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Medical Sports Rehabilitation Deep Learning System of Sports Injury Based on MRI Image Analysis

机译:基于MRI图像分析的体育康复深层学习体系

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摘要

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.
机译:本文提出了基于MRI图像分析的基于MRI图像分析的体育康复的体育康复深度学习体系。制备活动是在体育,培训和竞争之前故意进行的各种身体锻炼。它是从静态状态到人体的移动状态的过渡阶段。预备活动可以提高中枢神经系统的兴奋性,提高脑皮质分析和判断运动的能力,从而使运动更加协调和准确。同时,制备活性也可以改善呼吸和循环系统的功能,减少肌肉,韧性的粘性性质和肌肉收缩的速度和力量,以最大限度地提高物理运动和伤害预防竞选的能力准备好。因此,如何使用MRI映像来数值分析所提到的任务至关重要。我们整合了深度学习模型,提出了一种新颖的图像增强和识别模型,承接医疗体育康复系统的任务。实验结果证明了性能是强大的。

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