The utility of software-detected non-invasive tear break-up in comparison to fluorescein tear break-up measurements.

Purpose: The purpose of this study is to characterize and discuss the difference between software-detected non-invasive tear break-up time (NIBUT) and the traditional clinical method of fluorescein break-up time (FBUT).

Methods: Tear interferometry with the KOWA DR-1α (Kowa, Japan) and a standardized comprehensive ocular surface/tear evaluation were performed in 307 eyes. Software-detected NIBUT in the KOWA DR-1α images and the investigator-detected FBUT were compared.

Non-invasive and objective tear film breakup detection on interference color images using convolutional neural networks.

Purpose: Dry eye disease affects hundreds of millions of people worldwide and is one of the most common causes for visits to eye care practitioners. The fluorescein tear breakup time test is currently widely used to diagnose dry eye disease, but it is an invasive and subjective method, thus resulting in variability in diagnostic results. This study aimed to develop an objective method to detect tear breakup using the convolutional neural networks on the tear film images taken by the non-invasive device KOWA DR-1α.

Non-Invasive Tear Break-Up Detection with the Kowa DR-1α and Its Relationship to Dry Eye Clinical Severity.

The purpose of this study is to compare visual versus software detection of non-invasive tear break-up with the KOWA DR-1α tear interferometer and investigate the relationship between non-invasive tear break-up time (NIBUT) and dry eye clinical severity. Tear interferometry with the KOWA DR-1α, together with a standardized comprehensive ocular surface/tear evaluation, was performed on 348 consecutive eyes. Investigator visually detected or software detected non-invasive tear break-up and NIBUT were measured and compared on a subset of these examinations.