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The diagnostic accuracy of an intelligent and automated fundus disease image assessment system with lesion quantitative function (SmartEye) in diabetic patients

机译:糖尿病患者病变定量功能(Smarteye)智能和自动化眼底疾病图像评估系统的诊断准确性

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摘要

Abstract Background With the diabetes mellitus (DM) prevalence increasing annually, the human grading of retinal images to evaluate DR has posed a substantial burden worldwide. SmartEye is a recently developed fundus image processing and analysis system with lesion quantification function for DR screening. It is sensitive to the lesion area and can automatically identify the lesion position and size. We reported the diabetic retinopathy (DR) grading results of SmartEye versus ophthalmologists in analyzing images captured with non-mydriatic fundus cameras in community healthcare centers, as well as DR lesion quantitative analysis results on different disease stages. Methods This is a cross-sectional study. All the fundus images were collected from the Shanghai Diabetic Eye Study in Diabetics (SDES) program from Apr 2016 to Aug 2017. 19,904 fundus images were acquired from 6013 diabetic patients. The grading results of ophthalmologists and SmartEye are compared. Lesion quantification of several images at different DR stages is also presented. Results The sensitivity for diagnosing no DR, mild NPDR (non-proliferative diabetic retinopathy), moderate NPDR, severe NPDR, PDR (proliferative diabetic retinopathy) are 86.19, 83.18, 88.64, 89.59, and 85.02%. The specificity are 63.07, 70.96, 64.16, 70.38, and 74.79%, respectively. The AUC are PDR, 0.80 (0.79, 0.81); severe NPDR, 0.80 (0.79, 0.80); moderate NPDR, 0.77 (0.76, 0.77); and mild NPDR, 0.78 (0.77, 0.79). Lesion quantification results showed that the total hemorrhage area, maximum hemorrhage area, total exudation area, and maximum exudation area increase with DR severity. Conclusions SmartEye has a high diagnostic accuracy in DR screening program using non-mydriatic fundus cameras. SmartEye quantitative analysis may be an innovative and promising method of DR diagnosis and grading.
机译:摘要背景与糖尿病(DM)患病率每年增加,视网膜图像评估博士的人们已经构成了全世界大量负担。 Smarteye是最近开发的眼底图像处理和分析系统,具有用于DR筛选的病变量化功能。它对病变区域敏感,可以自动识别病变位置和尺寸。我们报道了Smarteye与眼科医生的糖尿病视网膜病变(DR)分级结果分析了社区医疗中心的非剖果眼镜捕获的图像,以及对不同疾病阶段的病变定量分析结果。方法这是一个横断面研究。从2016年4月到2017年4月,从上海糖尿病(SDES)计划中的上海糖尿病眼科研究所收集所有眼底图像。19,904个糖尿病患者收购了19,904个眼底图像。比较眼科医生和Smarteye的分级结果。还提出了不同DR阶段的几个图像的病变量化。导致诊断DR,轻度NPDR(非增殖性糖尿病视网膜病变),中等NPDR,严重NPDR,PDR(增殖性糖尿病视网膜病变)的敏感性为86.19,83.18,88.64,89.59和85.02%。特异性分别为63.07,70.96,64.16,70.38和74.79%。 AUC是PDR,0.80(0.79,0.81);严重的NPDR,0.80(0.79,0.80);中等NPDR,0.77(0.76,0.77);和温和的NPDR,0.78(0.77,0.79)。病变量化结果表明,总出血面积,最大出血面积,总渗出面积和最大渗出面积与严重程度博士增加。结论Smarteye使用非剖参性眼底相机在DR筛选方案中具有高诊断准确性。 Smarteye定量分析可能是DR诊断和分级的创新性和有希望的方法。

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