Automated Diabetic Retinopathy Screening and Monitoring Using Retinal Fundus Image Analysis.
Automated Diabetic Retinopathy Screening and Monitoring Using Retinal Fundus Image Analysis.
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DOI：
10.1177/1932296816628546
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发表时间：
2016-02-16
影响因子：
5
通讯作者：
Solanki, Kaushal
中科院分区：
文献类型：
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作者：
Bhaskaranand, Malavika;Ramachandra, Chaithanya;Solanki, Kaushal
背景技术背景：糖尿病视网膜病变（DR）是糖尿病的常见并发症，是西方世界工作年龄人群视力丧失的主要原因。DR在很大程度上是无症状的，但如果在早期发现，视力丧失的进展可以显着减缓。随着糖尿病人群的增加，迫切需要自动DR筛查和监测。为了满足这一日益增长的需求，在本文中，我们讨论了一种自动化DR筛查工具，并将其扩展为自动估计微动脉瘤（MA）周转，这是DR风险的潜在生物标志物。DR筛查工具自动分析来自患者就诊的彩色视网膜眼底图像的各种DR病理，并整理来自属于患者就诊的所有图像的信息，以生成患者眼底图像。等级筛选建议。MA营业额估计工具对准视网膜图像从一个病人的多次遭遇，定位MA，并进行MA动态分析，以评估新的，持续的，和消失的病变地图和估计MA turnover rates. RESULTS：DR筛选工具达到90%的灵敏度在63.2%的特异性上的数据集的40 542图像从5084患者遭遇从EyePACS筛选系统。在一个子集的7个纵向对的MA营业额估计工具确定新的和消失的MAs与100%的灵敏度和平均假阳性0.43和1.6分别。结论：所提出的自动化工具有可能解决日益增长的需要DR筛查和监测，从而节省视力的数百万糖尿病患者全球。
BACKGROUND: Diabetic retinopathy (DR)-a common complication of diabetes-is the leading cause of vision loss among the working-age population in the western world. DR is largely asymptomatic, but if detected at early stages the progression to vision loss can be significantly slowed. With the increasing diabetic population there is an urgent need for automated DR screening and monitoring. To address this growing need, in this article we discuss an automated DR screening tool and extend it for automated estimation of microaneurysm (MA) turnover, a potential biomarker for DR risk.METHODS: The DR screening tool automatically analyzes color retinal fundus images from a patient encounter for the various DR pathologies and collates the information from all the images belonging to a patient encounter to generate a patient-level screening recommendation. The MA turnover estimation tool aligns retinal images from multiple encounters of a patient, localizes MAs, and performs MA dynamics analysis to evaluate new, persistent, and disappeared lesion maps and estimate MA turnover rates.RESULTS: The DR screening tool achieves 90% sensitivity at 63.2% specificity on a data set of 40 542 images from 5084 patient encounters obtained from the EyePACS telescreening system. On a subset of 7 longitudinal pairs the MA turnover estimation tool identifies new and disappeared MAs with 100% sensitivity and average false positives of 0.43 and 1.6 respectively.CONCLUSIONS: The presented automated tools have the potential to address the growing need for DR screening and monitoring, thereby saving vision of millions of diabetic patients worldwide.