A Computer-Aided System for Ocular Myasthenia Gravis Diagnosis

作     者：Guanjie Liu Yan Wei Yunshen Xie Jianqiang Li Liyan Qiao Ji-jiang Yang Guanjie Liu;Yan Wei;Yunshen Xie;Jianqiang Li;Liyan Qiao;Ji-jiang Yang

作者机构：the Faculty of Information TechnologyBeijing University of TechnologyBeijing 100124China the Neurology DepartmentThe Second Affiliated Hospital of Tsinghua UniversityBeijing 100040China the Department of AutomationTsinghua UniversityBeijing 100084China 

出 版 物：《Tsinghua Science and Technology》 (清华大学学报（自然科学版（英文版）)

年 卷 期：2021年第26卷第5期

页      面：749-758页

核心收录：

学科分类：1002[医学-临床医学] 100204[医学-神经病学] 10[医学] 

主　　题：ocular myasthenia gravis computer-aided system semantic segmentation eyelid aspect ratio 

摘      要：The current mode of clinical aided diagnosis of Ocular Myasthenia Gravis(OMG)is time-consuming and laborious,and it lacks quantitative *** aided diagnostic system for OMG is proposed to solve this *** values calculated by the system include three clinical indicators:eyelid distance,sclera distance,and palpebra superior fatigability test *** the first two indicators,the semantic segmentation method was used to extract the pathological features of the patient s eye image and a semantic segmentation model was *** patient eye image was divided into three regions:iris,sclera,and *** indicators were calculated based on the position of the pixels in the segmentation *** the last indicator,a calculation method based on the Eyelid Aspect Ratio(EAR)is proposed;this method can better reflect the change of eyelid distance over *** system was evaluated based on the collected patient *** results show that the segmentation model achieves a mean Intersection-Over-Union(mIoU)value of 86.05%.The paired-sample T-test was used to compare the results obtained by the system and doctors,and the p values were all greater than ***,the system can reduce the cost of clinical diagnosis and has high application value.