用手机红眼反射图检测儿童视力问题，准确率达90%。
Early Detection of Visual Impairments at Home Using a Smartphone Red-Eye Reflex Test
- 基于深度学习分析儿童瞳孔图像，实现手机端自动筛查。
- 在未见数据上达到90%准确率，无需专业设备。
- 可指导用户获取最佳拍摄条件，适合家庭自检。
许多视觉障碍可通过年幼儿童的红眼反射图像检测。传统上，眼科医生在临床环境中进行所谓的布鲁克纳测试。得益于智能手机和人工智能的最新进展，现在可以使用移动设备复现布鲁克纳测试。本文介绍了在开发KidsVisionCheck免费应用过程中开展的首次研究，该应用利用手机红眼反射图像进行视力筛查。底层模型基于眼科医生标注的儿童瞳孔图像训练而成的深度神经网络。在未见测试数据上准确率达到90%，表现高度可靠，且无需专业设备。此外，我们能识别出最优数据采集条件，进而为用户提供即时反馈。总之，本工作标志着迈向全球可及的儿科视力筛查与早期干预的第一步。
原文摘要 · Abstract (English)
Numerous visual impairments can be detected in red-eye reflex images from young children. The so-called Bruckner test is traditionally performed by ophthalmologists in clinical settings. Thanks to the recent technological advances in smartphones and artificial intelligence, it is now possible to recreate the Bruckner test using a mobile device. In this paper, we present a first study conducted during the development of KidsVisionCheck, a free application that can perform vision screening with a mobile device using red-eye reflex images. The underlying model relies on deep neural networks trained on children's pupil images collected and labeled by an ophthalmologist. With an accuracy of 90% on unseen test data, our model provides highly reliable performance without the necessity of specialist equipment. Furthermore, we can identify the optimal conditions for data collection, which can in turn be used to provide immediate feedback to the users. In summary, this work marks a first step toward accessible pediatric vision screenings and early intervention for vision abnormalities worldwide.
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