Dr. Tongue: Sign-Oriented Multi-label Detection for Remote Tongue Diagnosis
Journal:
arXiv
Published Date:
Jan 6, 2025
Abstract
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.
