JMIR Publications

ABSTRACT

Background:

Strabismus, characterized by eye misalignment, impairs visual function and quality of life in children and adults. Traditional assessments demand specialized equipment and expertise, limiting access in underserved regions. Thus, innovative, accessible solutions are urgently needed to improve strabismus assessment and management.

Objective:

Strabismus measurement typically requires skilled clinicians and/or specialized equipment. Photographic strabismus measurement approaches have value in terms of accessibility and convenience of use. This study aimed to evaluate Eyeturn Cloud, a cloud-based AI system for measuring strabismus angles based on eye images under cover test conditions.

Methods:

Eyeturn Cloud web app uses AI models to recognize eyes, eye lid, iris, and then to segment iris precisely. It then computes strabismus based on ellipse fitting of iris boundary and corneal reflection. The system was evaluated in patients (without glasses) with manifest strabismus and control subjects. Clinicians measured eye deviations using prism alternate cover test (PACT) and also captured pictures of their eyes under alternate cover and unilateral cover conditions. The pictures were processed in Eyeturn Cloud.

Results:

79 subjects (age: 11.9±6.3 years, 15 esotropia, 55 exotropia, 9 normal) were enrolled, of which, data was available for 71 subjects (10.1% processing failure). The range of PACT strabismus magnitude was from 78 exo to 78 eso prism diopters (PD). According to linear regression, Eyeturn Cloud measurements were highly consistent with clinical measurements (R2=0.95, slope=0.91). Bland-Altman analysis revealed that 95% limits of agreement between the two measurements were [-20.2, 14.6] PD. A repeatability test with 15 subjects (4 photos each) found a 1.53PD standard deviation.

Conclusions:

The cloud AI web app can compute strabismus angles reliably under alternate and unilateral cover conditions.