%0 Journal Article
%T 基于改进Resnet50的角膜塑形镜智能验配方法研究<br>Research on Intelligent Fitting Method of Orthokeratology Lens Based on Improved Resnet50
%A 吴逸凡
%A 叶萍
%A 巩瑾琪
%A 陈齐欧
%A 常兆华
%J Software Engineering and Applications
%P 832-843
%@ 2325-2278
%D 2023
%I Hans Publishing
%R 10.12677/SEA.2023.126081
%X 通过彩色角膜地形图图像进行角膜塑形镜(Orthokeratology)智能验配，解决角膜塑形镜验配需要医生具备大量的验配经验的问题，本研究旨在提出一种基于改进的Resnet50网络的露晰得(Lucid)角膜塑形镜智能验配算法。在Resnet50的基础上，通过全局注意力机制GAM (Global Attention Mechanism)捕捉在通道、空间宽度和空间高度三个维度的特征，强化Resnet50对角膜塑形镜的三个参数进行图像分类的识别能力；并采用类别激活图(Class Activation Map, CAM)技术绘制模型关注角膜地形图特征的热力图。本文希望通过这种方法，为用户提供更加精准和个性化的角膜塑形镜验配方案。所提Resnet50-GAM模型在角膜塑形镜三个主要镜片参数，镜片直径(D)、环曲度(CP)以及平面镜片测量读数(镜片曲率半径)的图像分类上分别取得了89.2%、86.6%和79.1%的结果热力图显示Resnet50-GAM模型在分类过程中与验光师关注的点基本一致；所提Resnet50-GAM模型可用于边远地区、低收入和中等收入国家以及实验室设备资源有限的地区，以克服眼视光医生短缺的问题，提高角膜塑形镜的普及率。<br />
The aim of this study is to develop an intelligent fitting algorithm for orthokeratology lens based on color corneal topographic map images. Orthokeratology fitting requires a lot of experience from optometrists, which poses a challenge for many users. The aim of this study is to propose an intelligent matching algorithm of lucid plastic orthokeratology lens based on improved Resnet50 network. On the basis of Resnet50, the Global Attention Mechanism (GAM) captures the features in the three dimensions of channel, spatial width and spatial height, and strengthens the recognition ability of Resnet50 in image classification of the three parameters of orthokeratology mirror. Class Activation Map (CAM) was used to create a thermal map of corneal topographic features. Through this method, this paper hopes to provide users with more accurate and personalized orthokeratology lens fitting scheme. The Resnet50-GAM model has three main lens parameters in orthokeratology. The results of image classification of lens diameter (D), annular curvature (CP) and plane lens measurement reading (lens curvature radius) were 89.2%, 86.6% and 79.1%, respectively. Thermal maps showed that the Resnet50-GAM model was basically consistent with optometrists’ concerns in the classification process. The proposed Resnet50-GAM model can be used in remote areas, low - and middle-income countries, and areas with limited laboratory equipment resources to overcome the shortage of optometrists and increase the penetration of orthokeratology lens.
%K 角膜地形图，深度学习，注意力机制，角膜塑形镜，Resnet50<br>Corneal Topographic Map
%K Deep Learning
%K Attention Mechanism
%K Orthokeratology Lens
%K Resnet50
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=77137