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电影:确定视网膜上微动脉瘤的位置。

FILM: finding the location of microaneurysms on the retina.

作者信息

Akut Rohan R

机构信息

Department of Electronics and Telecommunication, MIT College of Engineering, Pune, India.

出版信息

Biomed Eng Lett. 2019 Nov 2;9(4):497-506. doi: 10.1007/s13534-019-00136-6. eCollection 2019 Nov.

Abstract

Diabetes retinopathy (DR) is one of the leading cause of blindness among people suffering from diabetes. It is a lesion based disease which starts off as small red spots on the retina. These small red lesions are known as microaneurysms (MA). These microaneurysms gradually increase in size as the DR progresses, which eventually leads to blindness. Thus, DR can be prevented at a very early stage by eliminating the retinal microaneurysms. However, elimination of MA is a two step process. The first step requires detecting the presence of MA on the retina. The second step involves pinpointing the location of MA on the retina. Even though, these two steps are interdependent, there is no model available that can perform both steps simultaneously. Most of the models perform the first step successfully, while the second step is performed by opthamologists manually. Hence we have proposed an object detection model that integrates the two steps by detecting (first step) and pinpointing (second step) the MA on the retina simultaneously. This would help the opthamologists in directly finding the exact location of MA on the retina, thereby simplifying the process and eliminating any manual intervention.

摘要

糖尿病视网膜病变(DR)是糖尿病患者失明的主要原因之一。它是一种基于病变的疾病,最初表现为视网膜上的小红点。这些小红斑被称为微动脉瘤(MA)。随着糖尿病视网膜病变的进展,这些微动脉瘤的大小会逐渐增加,最终导致失明。因此,通过消除视网膜微动脉瘤,可以在非常早期阶段预防糖尿病视网膜病变。然而,消除微动脉瘤是一个两步过程。第一步需要检测视网膜上微动脉瘤的存在。第二步涉及确定微动脉瘤在视网膜上的位置。尽管这两个步骤相互依存,但目前没有一个模型能够同时执行这两个步骤。大多数模型都能成功执行第一步,而第二步则由眼科医生手动完成。因此,我们提出了一种目标检测模型,该模型通过同时检测(第一步)和确定(第二步)视网膜上的微动脉瘤,将这两个步骤整合在一起。这将有助于眼科医生直接找到视网膜上微动脉瘤的确切位置,从而简化过程并消除任何人工干预。

相似文献

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FILM: finding the location of microaneurysms on the retina.电影:确定视网膜上微动脉瘤的位置。
Biomed Eng Lett. 2019 Nov 2;9(4):497-506. doi: 10.1007/s13534-019-00136-6. eCollection 2019 Nov.

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Microaneurysm detection using fully convolutional neural networks.基于全卷积神经网络的微动脉瘤检测
Comput Methods Programs Biomed. 2018 May;158:185-192. doi: 10.1016/j.cmpb.2018.02.016. Epub 2018 Feb 22.
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Automatic detection of microaneurysms in retinal fundus images.视网膜眼底图像中微动脉瘤的自动检测。
Comput Med Imaging Graph. 2017 Jan;55:106-112. doi: 10.1016/j.compmedimag.2016.08.001. Epub 2016 Aug 4.

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