VIOMA: Video-Based Intelligent Ocular Misalignment Assessment

The measurement of ocular alignment is critical for the diagnosis of strabismus. Current clinical methods for assessing ocular misalignment are subjective and frequently rely on the expertise of practitioners and the extent of patient cooperation. Computer-aided diagnosis methods in recent years have improved automation and precision of measurement, but still, fall short of the requirement of clinical practice. In this study, a video-based intelligent ocular misalignment assessment (VIOMA) system, was proposed to provide an objective, repeatable, user-friendly and highly-automated alternative modality for clinical ocular misalignment measurement, in which the automatic cover tests were performed under a control and motor unit, simultaneously the eye movements were tracked using a motion-capture module and assessed through video analysis techniques, determining the presence, type, and magnitude of eye deviation. For system evaluation, an automatic cover tests video dataset for strabismus (StrabismusACT-76) was established, which consists of data from 76 participants. The Bland-Altman plot, used to compare the results of the VIOMA system and human expert, showed a mean value of 1.26 prism diopter (PD) and a half-width of the 95% limit of agreement of ±7.17 PD. VIOMA system presented a mean absolute error of 3.04 PD in measuring the deviation magnitude, within a 5 PD error tolerance. Additionally, the system’s measurements were strongly correlated with that of video labeling with the mean value of -0.26 PD, a half-width of the 95% limit of agreement of ±3.56, and the average error of 1.31 PD. The experiment results indicated that the proposed method has the capability to offer accurate and efficient assessment of ocular misalignment. Note to Practitioners—The motivation behind this work stems from the need to develop an accurate and efficient system for automated ocular misalignment assessment. The subjectivity of manual cover test performed by examiners has led to variability in outcomes, and certain existing computerized methods have limitations in terms of automation, measurement accuracy, and applicability in clinical practice. Faced with these challenges, we proposed VIOMA, by establishing an apparatus for automatic implementation of cover tests and developing assessment algorithms based on strabismic video analysis. This system can objectively and precisely measure ocular misalignment, offering a promising practical solution for clinical intelligent diagnosis of strabismus. The VIOMA system’s potential applications are not limited to strabismus but may extend to other eye-related conditions and beyond.