Artificial Intelligence in Tongue Image Recognition

Hongli Chu, Yanhong Ji, Dingju Zhu, Zhanhao Ye, Jianbin Tan, Xianping Hou, Yujie Lin

Source Title: International Journal of Software Science and Computational Intelligence (IJSSCI)15(1)

ISSN: 1942-9045|EISSN: 1942-9037|EISBN13: 9781668479346|DOI: 10.4018/IJSSCI.328771

MLA

Chu, Hongli, et al. "Artificial Intelligence in Tongue Image Recognition." IJSSCI vol.15, no.1 2023: pp.1-25. http://doi.org/10.4018/IJSSCI.328771

APA

Chu, H., Ji, Y., Zhu, D., Ye, Z., Tan, J., Hou, X., & Lin, Y. (2023). Artificial Intelligence in Tongue Image Recognition. International Journal of Software Science and Computational Intelligence (IJSSCI), 15(1), 1-25. http://doi.org/10.4018/IJSSCI.328771

Chicago

Chu, Hongli, et al. "Artificial Intelligence in Tongue Image Recognition," International Journal of Software Science and Computational Intelligence (IJSSCI) 15, no.1: 1-25. http://doi.org/10.4018/IJSSCI.328771

Export Reference

Favorite Full-Issue Download

View Full Text HTML

View Full Text PDF

Abstract

Tongue image recognition is a traditional Chinese medicine diagnosis method, which uses the shape, color, and texture of the tongue to judge the health of the human body. With the rapid development of artificial intelligence technology, the application of artificial intelligence in the field of tongue recognition has been widely considered. Based on the intelligent analysis of tongue diagnosis in traditional Chinese medicine, this paper reviews the application progress of artificial intelligence in tongue image recognition in recent years and analyzes its potential and challenges in this field. Firstly, this paper introduces three steps of tongue image recognition, including tongue image acquisition, tongue image preprocessing, and tongue image feature analysis. The application of traditional methods and artificial intelligence methods in the whole process of tongue image recognition is reviewed, especially the tongue body segmentation, and the advantages and disadvantages of convolutional neural networks are analyzed and compared. Artificial intelligence can use technologies such as deep learning and computer vision to automatically analyze and extract features from tongue images. By constructing a tongue image recognition model, tongue shape, color, texture, and other features can be accurately recognized and quantitatively analyzed. Finally, this paper summarizes the problems existing in artificial intelligence in tongue image recognition and looks forward to the future developmental direction of this field. It can promote the modernization of TCM diagnostic methods, achieve early disease screening and prevention, personalized medicine and treatment optimization, and support medical research and knowledge accumulation. However, there is still a need for further validation and practice, with a focus on patient privacy and data security.