This study was to analyze the sport-induced ankle joint injury (AJI) images based on the neural network algorithms using the magnetic resonance imaging (MRI). 20 patients and 20 volunteers were included in the experimental and control groups, respectively. The hybrid diffusion equation (HDE) neural network (HDENN) algorithm was compared with the fully convolutional neural network (FCNN) and the FCNN preprocessing, and the HDE was applied to the MRI analysis of sport-induced AJI. The results showed that the total score of MRI image for the conventional position of the anterior talofibular ligament (ATFL) and posterior talofibular ligament (PTFL) was concentrated in 4 (55%) and 5 (65%), respectively. The number of patients with good prognosis with grade II injury (11 cases) was much higher than that of grade III injury (2 cases), and the number of patients with poor prognosis (4 cases) was lower than that of grade III injury (6 cases) (). Conventional MRI was recommended to observe the ATFL and PTFL, and the valgus position MRI was recommended for the calcaneofibular ligament (CFL); conservative treatment was recommended for patients with grades I and II AJI, but surgical treatment was recommended for patients with grade III AJI.

中文翻译：

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基于深度学习的MRI图像用于分析运动引起的踝关节损伤

这项研究的目的是使用磁共振成像（MRI）基于神经网络算法分析运动引起的踝关节损伤（AJI）图像。实验组和对照组分别包括20名患者和20名志愿者。将混合扩散方程（HDE）神经网络（HDENN）算法与全卷积神经网络（FCNN）和FCNN预处理进行了比较，并将HDE用于运动诱发的AJI的MRI分析。结果表明，MRI的总得分分别为前胫腓韧带（ATFL）和后腓胫韧带（PTFL）的常规位置，分别集中在4（55％）和5（65％）。Ⅱ级损伤预后良好的患者人数（11例）远高于Ⅲ级损伤（2例），）。建议使用常规MRI观察ATFL和PTFL，建议对跟腓韧带（CFL）进行外翻位MRI。对于I级和II级AJI患者，建议保守治疗，但对III级AJI患者，建议手术治疗。