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- W3138339983 abstract "The version exam is a test performed by specialists in ophthalmology to detect restrictions, paralysis, and disproportionate actions on the eye muscles in binocular movements, which is the simultaneous movement of the eyes. This test is commonly used in the detection, follow-up, and surgical planning of patients with strabismus. Strabismus is a condition in which the eyes do not have adequate alignment, generating several issues not only related to vision but also in social relations. This condition affects approximately 4% of the world’s population. In practice, the version exam is a subjective test, and the creation of a method that aims to automate the examination can help obtain a more objective result. Thus, this work presents an innovative computational method to perform the version examination automatically through face images. The proposed method is organized in seven main steps: (1) image acquisition; (2) preprocessing through a mean filter and Color Badger; (3) eye localization, based on skin segmentation and using Histograms of Oriented Gradients and Random Forest; (4) sclera segmentation, using statistical characteristics and the Random Forest classifier; (5) limbus localization, using as aid the segmented sclera; (6) eye corner localization, based on eye shape, analyzing the inner and outer eyes corners; and (7) version exam, using circle markers for each of the nine eye positions exams. The automatic measurement presented by the method was evaluated through the mean of the difference between the results provided by the method and the original versions measured by the specialist. When considering version, the proposed method obtained a mean accuracy and error of, respectively, 85.18% and 0.29 for the Medial Rectus muscle, 100% and 0 for the Lateral Rectus muscle, 86.9% and 0.47 for the Inferior Oblique muscle, 87.5% and 0.16 for the Superior Rectus muscle, 100% and 0 for the Superior Oblique muscle, and 95.23% and 0.28 for the Inferior Rectus muscle." @default.
- W3138339983 created "2021-03-29" @default.
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- W3138339983 date "2021-08-01" @default.
- W3138339983 modified "2023-10-01" @default.
- W3138339983 title "Automatic ocular version evaluation in images using random forest" @default.
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- W3138339983 doi "https://doi.org/10.1016/j.eswa.2021.114847" @default.
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