A New Software for Quantitative Measurement of Strabismus based on Digital Image

Kim, Taeyun; Seo, Sang-Sin; Kim, Young-Jae; Yang, Heekyung; Hwang, Jeong‐Min; Kim, Kwang Gi

doi:10.9717/kmms.2012.15.5.595

Cited by 8 publications

(1 citation statement)

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“…Assumption 2 was defined based on the average eye size that is used in clinical settings [ 18 , 19 ]. The radius of the limbus and corneal reflex point of the primary gaze image, which was further used as an indicator of the other images for the measurement, were defined.…”

Section: Methodsmentioning

confidence: 99%

Automated Mathematical Algorithm for Quantitative Measurement of Strabismus Based on Photographs of Nine Cardinal Gaze Positions

Kang

Yang

Kim

et al. 2022

BioMed Research International

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This study presents an automated algorithm that measures ocular deviation quantitatively using photographs of the nine cardinal points of gaze by means of deep learning (DL) and image processing techniques. Photographs were collected from patients with strabismus. The images were used as inputs for the DL segmentation models that segmented the sclerae and limbi. Subsequently, the images were registered for the mathematical algorithm. Two-dimensional sclera and limbus were modeled, and the corneal light reflex points of the primary gaze images were determined. Limbus recognition was performed to measure the pixel-wise distance between the corneal reflex point and limbus center. The segmentation models exhibited high performance, with 96.88% dice similarity coefficient (DSC) for the sclera segmentation and 95.71% DSC for the limbus segmentation. The mathematical algorithm was tested on two cranial nerve palsy patients to evaluate its ability to measure and compare ocular deviation in different directions. These results were consistent with the symptoms of such disorders. This algorithm successfully measured the distance of ocular deviation in patients with strabismus. With complementation in the dimension calculations, we expect that this algorithm can be used further in clinical settings to diagnose and measure strabismus at a low cost.

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Section: Methodsmentioning

confidence: 99%