Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/80651
Title: Intelligent evaluation of strabismus in videos based on an automated cover test
Authors: Zheng, Y
Fu, H
Li, R
Lo, WL
Chi, Z 
Feng, DD
Song, Z
Wen, D
Keywords: Automated cover tests
Deviation of strabismus
Intelligent evaluation
Pupil localization
Issue Date: 2019
Publisher: Molecular Diversity Preservation International (MDPI)
Source: Applied sciences, 2019, v. 9, no. 4, 731 How to cite?
Journal: Applied sciences 
Abstract: Strabismus is a common vision disease that brings about unpleasant influence on vision, as well as life quality. A timely diagnosis is crucial for the proper treatment of strabismus. In contrast to manual evaluation, well-designed automatic evaluation can significantly improve the objectivity, reliability, and efficiency of strabismus diagnosis. In this study, we have proposed an innovative intelligent evaluation system of strabismus in digital videos, based on the cover test. In particular, the video is recorded using an infrared camera, while the subject performs automated cover tests. The video is then fed into the proposed algorithm that consists of six stages: (1) eye region extraction, (2) iris boundary detection, (3) key frame detection, (4) pupil localization, (5) deviation calculation, and (6) evaluation of strabismus. A database containing cover test data of both strabismic subjects and normal subjects was established for experiments. Experimental results demonstrate that the deviation of strabismus can be well-evaluated by our proposed method. The accuracy was over 91%, in the horizontal direction, with an error of 8 diopters; and it was over 86% in the vertical direction, with an error of 4 diopters.
URI: http://hdl.handle.net/10397/80651
ISSN: 2076-3417
DOI: 10.3390/app9040731
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