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Designing a Subsystem for Creating a Three-dimensional Model of an Orthopedic Insole Based on Data from a Laser 3D Scanning of the Patient's Feet

机译:基于患者脚的激光3D扫描的数据,设计用于创建整形外观鞋垫三维模型的子系统

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The article discusses the use of artificial intelligence methods for the design of orthopedic structures intended for the therapy and treatment of various pathologies of the human skeleton. The development of a software package for creating a three-dimensional model of an orthopedic insole based on an image of a patient's foot obtained using a specialized 3D scanner is described. The model was built using a modified generative adversarial network (GAN) Pix2Pix. This type of networks is used for the first time to obtain medically significant results in the field of orthopedics. The problems associated with obtaining a dataset suitable for neural network modeling are considered. Methods are described that make it possible to bring this set to a form suitable for training and further use in neural network modeling. A software module-data loader has been designed and implemented, which allows converting a three-dimensional model into a numpy array of a depth map with subsequent use as a training set. For the preprocessing of the original images, the authors used a wide range of methods, including dimensionality reduction, noise suppression (Gaussian filter). The results of neural network modeling of an orthopedic insole are presented. The presence of a three-dimensional model of the insole will allow it to be made on an industrial milling machine or printed on a printer using specialized medical material.
机译:本文讨论了人工智能方法对拟骨结构的设计,用于治疗和治疗人骨骼的各种病理。描述基于使用专用3D扫描仪获得的患者脚的图像来创建矫形鞋底孔的三维模型的软件包的开发。该模型是使用改进的生成对冲网络(GaN)PIX2PIX构建的。这种类型的网络首次使用,以获得骨科领域的医学上显着的结果。考虑了与获得适合神经网络建模的数据集相关联的问题。描述了方法,使得可以使该设置为适合于训练和进一步用于神经网络建模的形式。设计和实现了软件模块数据加载器,其允许将三维模型转换为深度映射的Numpy数组,随后用作训练集。为了预处理原始图像,作者使用了广泛的方法,包括减少噪声抑制(高斯滤波器)。提出了神经网络建模的神经网络建模的结果。鞋底孔的三维模型的存在将使它在工业铣床上制作或在使用专门的医疗材料上印刷在打印机上。

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