论文标题
基于准形式的几何形状基于局部头皮的局部变形分析儿童期OSA分类
Quasi-conformal Geometry based Local Deformation Analysis of Lateral Cephalogram for Childhood OSA Classification
论文作者
论文摘要
颅面轮廓是阻塞性睡眠呼吸暂停（OSA）的解剖学原因之一。通过医学研究，头部测量法提供了有关患者骨骼结构和软组织的信息。在这项工作中，提出了一种基于准统一形状几何形状的局部变形信息进行头皮测量学分析的新方法，以进行OSA分类。我们的研究是基于60个病例对照对的回顾性分析，并具有可访问的侧面头部计量学和多个术语（PSG）数据。通过使用准符合形式的几何形状研究近15个地标点附近的局部变形，并将结果与地标点之间的三个线性距离相结合，每个受试者总共获得了1218个信息特征。建立了基于L2规范的分类模型。在实验下，我们提出的模型达到了92.5％的测试精度。
Craniofacial profile is one of the anatomical causes of obstructive sleep apnea(OSA). By medical research, cephalometry provides information on patients' skeletal structures and soft tissues. In this work, a novel approach to cephalometric analysis using quasi-conformal geometry based local deformation information was proposed for OSA classification. Our study was a retrospective analysis based on 60 case-control pairs with accessible lateral cephalometry and polysomnography (PSG) data. By using the quasi-conformal geometry to study the local deformation around 15 landmark points, and combining the results with three linear distances between landmark points, a total of 1218 information features were obtained per subject. A L2 norm based classification model was built. Under experiments, our proposed model achieves 92.5% testing accuracy.
