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基于从人眼角膜缘确定动态距离的移动视力测试应用程序。

A mobile vision testing application based on dynamic distance determination from the human corneal limbus.

机构信息

Stanford University, USA.

出版信息

Health Informatics J. 2020 Dec;26(4):3037-3055. doi: 10.1177/1460458220958537. Epub 2020 Sep 30.

Abstract

Here we present a mobile application that accurately determines the distance between an optical sensor and the human corneal limbus for visual acuity assessment. The application uses digital image processing and randomized circle detection to locate the cornea. Then, a reference scaling measurement is employed to calculate distance from the sensor to a user. To determine accuracy and generalizability, testing was conducted both with 200 static images, 25 images each of males and females for four ethnic groups from a facial image database, and live image streams from a test subject. Average absolute corneal radius error over 10 trials for the static images was 6.36%, while average absolute distance error for the live image streams was less than 1%. Subsequently, distance measurements were used to scale letter sizes for a Snellen Chart-based visual acuity assessment. This system enables monitoring of chronic retinal diseases, as patients can quickly and accurately measure their visual acuity through the mobile eye exam suite.

摘要

我们在此展示了一个移动应用程序,它可以准确地确定光学传感器与人眼角膜缘之间的距离,用于视力评估。该应用程序使用数字图像处理和随机圆检测来定位角膜。然后,使用参考比例测量来计算传感器到用户的距离。为了确定准确性和通用性,我们使用 200 张静态图像、来自面部图像数据库的四个族群的 25 张男性和女性图像以及测试对象的实时图像流进行了测试。静态图像的 10 次试验中平均绝对角膜半径误差为 6.36%,而实时图像流的平均绝对距离误差小于 1%。随后,使用距离测量值来缩放基于 Snellen 图表的视力评估的字母大小。该系统可用于监测慢性视网膜疾病,因为患者可以通过移动眼科检查套件快速准确地测量自己的视力。

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