用AI自动分析儿童高度近视眼底血管变化，发现血管角度与分支系数显著异常。
AI-Based Fully Automatic Analysis of Retinal Vascular Morphology in Pediatric High Myopia
- 融合CNN与注意力模块，自动识别、分割并测量眼底血管关键参数。
- 高度近视者血管主干角和分支系数明显降低，静脉系统变化更显著。
- 模型准确率达94.19%，适合眼科疾病筛查与研究使用。
目的：基于人工智能设计自动化软件，研究不同近视阶段眼底血管结构的变化。方法：纳入中国儿童医学中心1324名儿童，获取2366张高质量眼底图像及对应屈光参数，计算球镜等效度（SER）。提出一种结合卷积神经网络（CNN）与注意力模块的数据分析模型，用于图像分类、血管分割及测量主干角（MA）、分支角（BA）、分叉边缘角（BEA）和分叉边缘系数（BEC）。通过单因素方差分析比较正常眼底、低度近视、中度近视和高度近视组间参数差异。结果：正常组有279张（12.38%），高度近视组有384张（16.23%）。相比正常眼底，各近视组的MA显著减小（P = 0.006, 0.004, 0.019），静脉系统尤为明显（P < 0.001）；BEA则呈非比例下降（P < 0.001）。进一步分析显示，高度近视组动脉分支角（BA）低于其他组（P = 0.032，95% CI: 0.22–4.86），而静脉分支角升高（P = 0.026），且高度近视组的BEC高于低、中度近视组。当模型损失函数收敛至0.09时，分类准确率达94.19%。
原文摘要 · Abstract (English)
Purpose: To investigate the changes in retinal vascular structures associated various stages of myopia by designing automated software based on an artif intelligencemodel. Methods: The study involved 1324 pediatric participants from the National Childr Medical Center in China, and 2366 high-quality retinal images and correspon refractive parameters were obtained and analyzed. Spherical equivalent refrac(SER) degree was calculated. We proposed a data analysis model based c combination of the Convolutional Neural Networks (CNN) model and the atter module to classify images, segment vascular structures, and measure vasc parameters, such as main angle (MA), branching angle (BA), bifurcation edge al(BEA) and bifurcation edge coefficient (BEC). One-way ANOVA compared param measurements betweenthenormalfundus,lowmyopia,moderate myopia,and high myopia group. Results: There were 279 (12.38%) images in normal group and 384 (16.23%) images in the high myopia group. Compared normal fundus, the MA of fundus vessels in different myopic refractive groups significantly reduced (P = 0.006, P = 0.004, P = 0.019, respectively), and performance of the venous system was particularly obvious (P<0.001). At the sa time, the BEC decreased disproportionately (P<0.001). Further analysis of fundus vascular parameters at different degrees of myopia showed that there were also significant differences in BA and branching coefficient (BC). The arterial BA value of the fundus vessel in the high myopia group was lower than that of other groups (P : 0.032, 95% confidence interval [Ci], 0.22-4.86), while the venous BA values increased(P = 0.026). The BEC values of high myopia were higher than those of low and moderate myopia groups. When the loss function of our data classification model converged to 0.09,the model accuracy reached 94.19%
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。