Visceral condition assessment through digital tongue image analysis
Traditional Chinese medicine (TCM) has long utilized tongue diagnosis as a crucial method for assessing internal visceral condition. This study aims to modernize this ancient practice by developing an automated system for analyzing tongue images in relation to the five organs, corresponding to the h...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Artificial Intelligence |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/frai.2024.1501184/full |
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| author | Siu Cheong Ho Yiliang Chen Yao Jie Xie Wing-Fai Yeung Shu-Cheng Chen Jing Qin |
| author_facet | Siu Cheong Ho Yiliang Chen Yao Jie Xie Wing-Fai Yeung Shu-Cheng Chen Jing Qin |
| author_sort | Siu Cheong Ho |
| collection | DOAJ |
| description | Traditional Chinese medicine (TCM) has long utilized tongue diagnosis as a crucial method for assessing internal visceral condition. This study aims to modernize this ancient practice by developing an automated system for analyzing tongue images in relation to the five organs, corresponding to the heart, liver, spleen, lung, and kidney—collectively known as the “five viscera” in TCM. We propose a novel tongue image partitioning algorithm that divides the tongue into four regions associated with these specific organs, according to TCM principles. These partitioned regions are then processed by our newly developed OrganNet, a specialized neural network designed to focus on organ-specific features. Our method simulates the TCM diagnostic process while leveraging modern machine learning techniques. To support this research, we have created a comprehensive tongue image dataset specifically tailored for these five visceral pattern assessment. Results demonstrate the effectiveness of our approach in accurately identifying correlations between tongue regions and visceral conditions. This study bridges TCM practices with contemporary technology, potentially enhancing diagnostic accuracy and efficiency in both TCM and modern medical contexts. |
| format | Article |
| id | doaj-art-c90ea7d1e447406d8d89d4e1dbf3d01d |
| institution | Kabale University |
| issn | 2624-8212 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Artificial Intelligence |
| spelling | doaj-art-c90ea7d1e447406d8d89d4e1dbf3d01d2025-01-06T06:59:15ZengFrontiers Media S.A.Frontiers in Artificial Intelligence2624-82122025-01-01710.3389/frai.2024.15011841501184Visceral condition assessment through digital tongue image analysisSiu Cheong HoYiliang ChenYao Jie XieWing-Fai YeungShu-Cheng ChenJing QinTraditional Chinese medicine (TCM) has long utilized tongue diagnosis as a crucial method for assessing internal visceral condition. This study aims to modernize this ancient practice by developing an automated system for analyzing tongue images in relation to the five organs, corresponding to the heart, liver, spleen, lung, and kidney—collectively known as the “five viscera” in TCM. We propose a novel tongue image partitioning algorithm that divides the tongue into four regions associated with these specific organs, according to TCM principles. These partitioned regions are then processed by our newly developed OrganNet, a specialized neural network designed to focus on organ-specific features. Our method simulates the TCM diagnostic process while leveraging modern machine learning techniques. To support this research, we have created a comprehensive tongue image dataset specifically tailored for these five visceral pattern assessment. Results demonstrate the effectiveness of our approach in accurately identifying correlations between tongue regions and visceral conditions. This study bridges TCM practices with contemporary technology, potentially enhancing diagnostic accuracy and efficiency in both TCM and modern medical contexts.https://www.frontiersin.org/articles/10.3389/frai.2024.1501184/fulltongue diagnosisinspection of the tongueChinese medicinefive visceradeep learningmulti-task learning |
| spellingShingle | Siu Cheong Ho Yiliang Chen Yao Jie Xie Wing-Fai Yeung Shu-Cheng Chen Jing Qin Visceral condition assessment through digital tongue image analysis Frontiers in Artificial Intelligence tongue diagnosis inspection of the tongue Chinese medicine five viscera deep learning multi-task learning |
| title | Visceral condition assessment through digital tongue image analysis |
| title_full | Visceral condition assessment through digital tongue image analysis |
| title_fullStr | Visceral condition assessment through digital tongue image analysis |
| title_full_unstemmed | Visceral condition assessment through digital tongue image analysis |
| title_short | Visceral condition assessment through digital tongue image analysis |
| title_sort | visceral condition assessment through digital tongue image analysis |
| topic | tongue diagnosis inspection of the tongue Chinese medicine five viscera deep learning multi-task learning |
| url | https://www.frontiersin.org/articles/10.3389/frai.2024.1501184/full |
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