An annotated dataset of tongue images

To develop a non-invasive assessment tool using machine learning in supporting a timely, accurate diagnosis in the elderly, we created an annotated dataset of 668 tongue images collected from hospitalized geriatric patients in a tertiary hospital in Shanghai, China. Images were captured via a light-field camera using CIELAB color space (to simulate human visual perception) and then were manually labeled by a panel of subject matter experts after chart reviewing patients’ clinical information documented in the hospital’s information system.

为开发一款可依托机器学习辅助老年患者实现及时、精准诊断的无创评估工具，我们构建了一套标注数据集：该数据集包含668张舌部图像，采集自中国上海某三级医院的住院老年患者。图像通过光场相机（light-field camera）采集，采用CIELAB色彩空间（CIELAB color space）以模拟人类视觉感知；随后由领域专家小组结合医院信息系统存档的患者临床信息完成病历审阅，并进行手动标注。