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VR based strabismus diagnosis using image processing (Conference Presentation)
Author(s): Yinan Miao; Hweekwon Jung; Gyuhae Park; Hwan Heo

Paper Abstract

Strabismus is an eye movement disorder that the eyes do not properly align with each other when looking at an object. This disorder is usually caused by muscle malfunctions, nerve problems or injuries. Currently, the ophthalmic prism with two nonparallel planes is used to diagnose the strabismus angle. The light into one eye is refracted when passing through the prism, which adjusts both eyes to looking forward. The strabismus angle is then identified after checking the parameter of the prism. However, the whole process is operated depending on the doctors’ experience which shows somewhat low efficiency and low accuracy. In this study, an automated strabismus diagnosis technique using VR device is developed. A specially-designed VR is built to simulate the normal strabismus diagnosis steps, in which screens are controlled to change alternately between on and off. The eye motions are tracked by two IR cameras by an image-processing based pupil tracking technique. After tracking the motion of the pupil, the position information is converted to the strabismus angle by considering the eyeball diameter. With this process, the strabismus angle is accurately and automatically identified using a unique feature recognition technique. To demonstrate the performance of this technique, experiments are carried out on various persons, including strabismus patients. The results are compared to the doctor’s diagnosis. The results show that this technique could identify the strabismus angle with high accuracy and high efficiency.

Paper Details

Date Published: 29 March 2019
Proc. SPIE 10970, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2019, 109701G (29 March 2019); doi: 10.1117/12.2514254
Show Author Affiliations
Yinan Miao, Chonnam National Univ. (Korea, Republic of)
Hweekwon Jung, Chonnam National Univ. (Korea, Republic of)
Gyuhae Park, Chonnam National Univ. (Korea, Republic of)
Hwan Heo, Chonnam National Univ. (Korea, Republic of)

Published in SPIE Proceedings Vol. 10970:
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2019
Jerome P. Lynch; Haiying Huang; Hoon Sohn; Kon-Well Wang, Editor(s)

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