Dry Eye Disease (DED) is one of the most common ocular diseases: over five percent of US adults suffer from DED. Tear film instability is a known factor for DED, and is thought to be regulated in large part by the thin lipid layer that covers and stabilizes the tear film. In order to aid eye related disease diagnosis, this work proposes a novel paradigm in using computer vision techniques to numerically analyze the tear film lipid layer (TFLL) spread. Eleven videos of the tear film lipid layer spread are collected with a micro-interferometer and a subset are annotated. A tracking algorithm relying on various pillar computer vision techniques is developed. Our method can be found at https://easytear-dev.github.io/.

翻译：干眼病(DED)是最常见的眼科疾病之一:超过5%的美国成年人患有DED。 眼泪膜不稳定是DED已知的一个因素,据信在很大程度上由覆盖和稳定眼泪膜的薄脂层调节。 为了帮助诊断与眼睛有关的疾病,这项工作提出了使用计算机视觉技术从数字上分析破泪膜脂层(TFLL)扩散的新型范例。11部关于裂泪膜脂层扩散的视频用微干涉仪收集,一个子集有附加说明。开发了依赖各种支柱计算机视觉技术的跟踪算法。我们的方法可以在https://seaitear-dev.github.io/上找到。