人工智能在舌头图像识别中的应用

IF 2.4 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Software Science and Computational Intelligence-IJSSCI Pub Date : 2023-08-25 DOI:10.4018/ijssci.328771
Hongli Chu, Y. Ji, Dingju Zhu, Zhanhao Ye, Jianbin Tan, Xianping Hou, Yujie Lin
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引用次数: 0

摘要

舌头图像识别是一种中医诊断方法,它利用舌头的形状、颜色和纹理来判断人体的健康状况。随着人工智能技术的飞速发展,人工智能在舌头识别领域的应用受到了广泛的关注。本文在对中医舌诊智能分析的基础上,综述了近年来人工智能在舌诊图像识别中的应用进展,分析了人工智能在该领域的潜力和面临的挑战。本文首先介绍了舌头图像识别的三个步骤:舌头图像采集、舌头图像预处理和舌头图像特征分析。综述了传统方法和人工智能方法在舌头图像识别全过程中的应用,特别是舌体分割,并对卷积神经网络的优缺点进行了分析比较。人工智能可以利用深度学习和计算机视觉等技术,自动分析和提取舌头图像的特征。通过构建舌头图像识别模型,可以对舌头的形状、颜色、纹理等特征进行准确的识别和定量分析。最后,本文总结了人工智能在舌头图像识别中存在的问题,并展望了该领域未来的发展方向。它可以促进中医诊断方法的现代化,实现疾病的早期筛查和预防,个性化医疗和治疗优化,支持医学研究和知识积累。然而,仍然需要进一步的验证和实践,重点是患者隐私和数据安全。
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Artificial Intelligence in Tongue Image Recognition
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.
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