Virtual Instrument used for the Evaluation of Extraocular Motility

Pop, Nicoleta; Demea, Anca; Gherman, Bogdan; Pîslă, Doina; Holonec, Rodica

doi:10.1109/ehb47216.2019.8969909

Cited by 1 publication

(2 citation statements)

References 6 publications

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“…In [6], the authors adopted eye-position metrics using video-based clinical techniques. The system proposed by [7] uses a virtual instrument to experimentally detect extraocular motility using Hess test; a group of features are proposed to characterize the extraocular data to detect paralytic strabismus. The system proposed by [8] detects strabismus using convolutional neural networks; an eye tracker detects eye motion and feeds an image to the neural network.…”

Section: Related Workmentioning

confidence: 99%

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Methodology for Detecting Strabismus through Video Analysis and Intelligent Mining Techniques

Mengash¹,

Mahmoud²

2021

Computers, Materials &Amp; Continua

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Strabismus is a medical condition that is defined as the lack of coordination between the eyes. When Strabismus is detected at an early age, the chances of curing it are higher. The methods used to detect strabismus and measure its degree of deviation are complex and time-consuming, and they always require the presence of a physician. In this paper, we present a method of detecting strabismus and measuring its degree of deviation using videos of the patient's eye region under a cover test. Our method involves extracting features from a set of training videos (training corpora) and using them to build a classifier. A decision tree (ID3) is built using labeled cases from actual strabismus diagnosis. Patterns are extracted from the corresponding videos of patients, and an association between the extracted features and actual diagnoses is established. Matching Rules from the correlation plot are used to predict diagnoses for future patients. The classifier was tested using a set of testing videos (testing corpora). The results showed 95.9% accuracy, 4.1% were light cases and could not be detected correctly from the videos, half of them were false positive and the other half was false negative.

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Section: Related Workmentioning

confidence: 99%

“…Computerized strabismus tests are now available, however. Existing computer methods are either image based or video-based, both categories use eye-tracking, which can be obtained from sequential images or video frames of the patient's eyes [6,7].…”

Section: Introductionmentioning

confidence: 99%

Methodology for Detecting Strabismus through Video Analysis and Intelligent Mining Techniques

Mengash¹,

Mahmoud²

2021

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

Virtual Instrument used for the Evaluation of Extraocular Motility

Cited by 1 publication

References 6 publications

Methodology for Detecting Strabismus through Video Analysis and Intelligent Mining Techniques

Methodology for Detecting Strabismus through Video Analysis and Intelligent Mining Techniques

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