用AI实现低成本眼周测量，支持多设备离线使用
Glorbit: A Modular, Web-Based Platform for AI Based Periorbital Measurement in Low-Resource Settings
- 基于DeepLabV3的分割模型，集成在可复用的浏览器应用中
- 15人测试中全流程无错误，平均耗时101.7秒，准确率100%
- 适合资源匮乏地区医生使用，支持数据安全上传与未来临床拓展
眼周测量如睑裂高度、角膜反射距离（MRD1/2）和巩膜显露量对上睑下垂等眼睑疾病的诊断至关重要。我们开发了Glorbit，一款轻量级、基于浏览器的AI应用，用于低资源临床环境下的自动化眼周距离测量。该应用将DeepLabV3分割模型嵌入模块化流程，结合安全的专属谷歌云存储。Glorbit支持离线模式、本地预处理及通过Firebase认证登录上传数据。通过15名志愿者的模拟注册研究评估可用性、跨平台兼容性和部署可行性。所有测试会话均顺利完成从元数据录入、图像采集、分割到上传的全流程，未出现错误。Glorbit在笔记本、平板和手机上的主流浏览器中均可正常运行。分割模型在所有图像上均成功执行。平均会话时间为101.7秒（标准差：17.5）。可用性调查评分（1-5分制）普遍较高：直观性与效率为5.0，流程清晰度4.8，输出可信度4.9，临床实用性4.9。Glorbit提供了一种功能完整、可扩展的眼周标准化测量解决方案，支持安全数据收集，未来或可用于实时分诊工具与多模态AI眼科整形系统。工具地址：https://glorbit.app
原文摘要 · Abstract (English)
Periorbital measurements such as margin reflex distances (MRD1/2), palpebral fissure height, and scleral show are essential in diagnosing and managing conditions like ptosis and eyelid disorders. We developed Glorbit, a lightweight, browser-based application for automated periorbital distance measurement using artificial intelligence, designed for use in low-resource clinical settings. The app integrates a DeepLabV3 segmentation model into a modular pipeline with secure, site-specific Google Cloud storage. Glorbit supports offline mode, local preprocessing, and cloud upload via Firebase-authenticated logins. We evaluated usability, cross-platform compatibility, and deployment readiness through a simulated enrollment study of 15 volunteers. The app completed the full workflow -- metadata entry, image capture, segmentation, and upload -- on all tested sessions without error. Glorbit successfully ran on laptops, tablets, and mobile phones across major browsers. The segmentation model succeeded on all images. Average session time was 101.7 seconds (standard deviation: 17.5). Usability survey scores (1-5 scale) were uniformly high: intuitiveness and efficiency (5.0), workflow clarity (4.8), output confidence (4.9), and clinical utility (4.9). Glorbit provides a functional, scalable solution for standardized periorbital measurement in diverse environments. It supports secure data collection and may enable future development of real-time triage tools and multimodal AI-driven oculoplastics. Tool available at: https://glorbit.app
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