{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T20:14:40Z","timestamp":1791490480710,"version":"4.3.4"},"reference-count":20,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T00:00:00Z","timestamp":1717113600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["THC"],"published-print":{"date-parts":[[2024,5,31]]},"abstract":"<jats:p>BACKGROUND: Computer-aided tongue and face diagnosis technology can make Traditional Chinese Medicine (TCM) more standardized, objective and quantified. However, many tongue images collected by the instrument may not meet the standard in clinical applications, which affects the subsequent quantitative analysis. The common tongue diagnosis instrument cannot determine whether the patient has fully extended the tongue or collected the face. OBJECTIVE: This paper proposes an image quality control algorithm based on deep learning to verify the eligibility of TCM tongue diagnosis images. METHODS: We firstly gathered enough images and categorized them into five states. Secondly, we preprocessed the training images. Thirdly, we built a ResNet34 model and trained it by the transfer learning method. Finally, we input the test images into the trained model and automatically filter out unqualified images and point out the reasons. RESULTS: Experimental results show that the model\u2019s quality control accuracy rate of the test dataset is as high as 97.06%. Our methods have the strong discriminative power of the learned representation. Compared with previous studies, it can guarantee subsequent tongue image processing. CONCLUSIONS: Our methods can guarantee the subsequent quantitative analysis of tongue shape, tongue state, tongue spirit, and facial complexion.<\/jats:p>","DOI":"10.3233\/thc-248018","type":"journal-article","created":{"date-parts":[[2024,5,14]],"date-time":"2024-05-14T11:01:33Z","timestamp":1715684493000},"page":"207-216","source":"Crossref","is-referenced-by-count":10,"title":["Intelligent quality control of traditional chinese medical tongue diagnosis images based on deep learning"],"prefix":"10.1177","volume":"32","author":[{"given":"Xuezhong","family":"Zhou","sequence":"first","affiliation":[{"name":"Community Health Center of Tianping Subdistrict, Xuhui District, Shanghai, China"},{"name":"Community Health Center of Tianping Subdistrict, Xuhui District, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenxi","family":"Li","sequence":"additional","affiliation":[{"name":"Community Health Center of Tianping Subdistrict, Xuhui District, Shanghai, China"},{"name":"Community Health Center of Tianping Subdistrict, Xuhui District, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hai","family":"Su","sequence":"additional","affiliation":[{"name":"Community Health Center of Tianping Subdistrict, Xuhui District, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhixian","family":"Tang","sequence":"additional","affiliation":[{"name":"College of Medical Imaging, Shanghai University of Medicine and Health Sciences, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Li","sequence":"additional","affiliation":[{"name":"College of Medical Instrumentation, Shanghai University of Medicine and Health Sciences, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yijie","family":"Li","sequence":"additional","affiliation":[{"name":"College of Information Technology, Shanghai Ocean University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2132-5342","authenticated-orcid":false,"given":"Jiawei","family":"Hou","sequence":"additional","affiliation":[{"name":"Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3586-7934","authenticated-orcid":false,"given":"Xun","family":"Sun","sequence":"additional","affiliation":[{"name":"Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","reference":[{"key":"10.3233\/THC-248018_ref1","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/j.eujim.2015.06.006","article-title":"An objective review of the technological developments for radial pulse diagnosis in Traditional Chinese 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