标题： Tongue博士：面向符号的多标签远程舌头诊断 显示英文标题

标题： Dr. Tongue: Sign-Oriented Multi-label Detection for Remote Tongue Diagnosis

摘要： 舌诊是西方医学和传统中医中的重要工具，通过分析舌部特征为患者健康提供关键见解。新冠疫情加剧了对准确远程医疗评估的需求，强调了通过远程医疗进行精确舌部特征识别的重要性。为了解决这一问题，我们提出了一种面向符号的多标签属性检测框架。我们的方法首先包含一个自适应舌部特征提取模块，用于标准化舌部图像并减少环境因素的影响。随后是一个面向符号的网络（SignNet），用于识别特定的舌部属性，模拟经验丰富的执业医师的诊断过程，从而实现全面的健康评估。为了验证我们的方法，我们开发了一个专门用于远程医疗的广泛舌部图像数据集。与现有数据集不同，我们的数据集专为远程诊断设计，并具有全面的属性标签。该数据集将公开可用，为研究提供宝贵的资源。初步测试已显示出在检测各种舌部属性方面的准确性提高，突显了我们的框架作为远程医疗评估重要工具的潜力。 显示英文摘要

摘要： Tongue diagnosis is a vital tool in Western and Traditional Chinese Medicine, providing key insights into a patient's health by analyzing tongue attributes. The COVID-19 pandemic has heightened the need for accurate remote medical assessments, emphasizing the importance of precise tongue attribute recognition via telehealth. To address this, we propose a Sign-Oriented multi-label Attributes Detection framework. Our approach begins with an adaptive tongue feature extraction module that standardizes tongue images and mitigates environmental factors. This is followed by a Sign-oriented Network (SignNet) that identifies specific tongue attributes, emulating the diagnostic process of experienced practitioners and enabling comprehensive health evaluations. To validate our methodology, we developed an extensive tongue image dataset specifically designed for telemedicine. Unlike existing datasets, ours is tailored for remote diagnosis, with a comprehensive set of attribute labels. This dataset will be openly available, providing a valuable resource for research. Initial tests have shown improved accuracy in detecting various tongue attributes, highlighting our framework's potential as an essential tool for remote medical assessments.