{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:35:38Z","timestamp":1792787738220,"version":"4.5.0"},"reference-count":45,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62104034"],"award-info":[{"award-number":["62104034"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Central Guidance Local Science and Technology Development Project","award":["246Z2002G"],"award-info":[{"award-number":["246Z2002G"]}]},{"DOI":"10.13039\/501100003787","name":"Natural Science Foundation of Hebei Province","doi-asserted-by":"publisher","award":["F2024501044"],"award-info":[{"award-number":["F2024501044"]}],"id":[{"id":"10.13039\/501100003787","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["DIGITAL HEALTH"],"published-print":{"date-parts":[[2025,4]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Traditional Chinese medicine (TCM) tongue diagnosis, through the comprehensive observation of tongue\u2019s diverse characteristics, allows an understanding of the state of the body\u2019s viscera as well as Qi and blood levels. Automatic tongue image recognition methods could support TCM practitioners by providing auxiliary diagnostic suggestions. However, most learning-based methods often address a narrow scope of the tongue\u2019s attributes, failing to fully exploit the information contained within the tongue images.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To classify multifaceted tongue characteristics, and fully utilize the latent correlation information between tongue segmentation and classification tasks, we proposed a multi-task joint learning network for simultaneous tongue body segmentation and multi-label Classification, named SSC-Net.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Firstly, the shared feature encoder extracts features for both segmentation and classification tasks, where the segmentation result is utilized to mask redundant features that may impede classification accuracy. Subsequently, the ROI extraction module locates and extracts the tongue body region, and the feature fusion module combines tongue body features from bottom to top. Finally, a fine-grained classification module is employed for multi-label classification on multiple tongue characteristics.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>To evaluate the performance of the SSC-Net, we collected a tongue image dataset, BUCM, and conducted extensive experiments on it. The experimental results show that the proposed method when segmenting and classifying simultaneously, achieved 0.9943 DSC for the segmentation task, 92.02 mAP, and 0.851 overall F1-score for the classification task.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The proposed method can effectively classify multiple tongue characteristics with the support of the multi-task learning strategy and the integration of a fine-grained classification module. Code is available here.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/20552076251343696","type":"journal-article","created":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T10:29:41Z","timestamp":1747823381000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":45,"title":["SSC-Net: A multi-task joint learning network for tongue image segmentation and multi-label classification"],"prefix":"10.1177","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3323-7322","authenticated-orcid":false,"given":"Xiaopeng","family":"Sha","sequence":"first","affiliation":[{"name":"Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology, Qinhuangdao, China"},{"name":"School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zheng","family":"Guan","sequence":"additional","affiliation":[{"name":"School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Wang","sequence":"additional","affiliation":[{"name":"The Third School of Clinical Medicine, Beijing University of Chinese Medicine, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinglu","family":"Han","sequence":"additional","affiliation":[{"name":"Department of Traditional Chinese Medicine, Second Hospital of Shandong University, Jinan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaojun","family":"Chen","sequence":"additional","affiliation":[{"name":"The Third School of Clinical Medicine, Beijing University of Chinese Medicine, Beijing, China"},{"name":"Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,5,21]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1177\/20552076231191044"},{"key":"e_1_3_3_3_2","first-page":"101834","article-title":"Development of a tongue image-based machine learning tool for the diagnosis of gastric cancer: a prospective multicentre clinical cohort study","volume":"57","author":"Yuan L","year":"2023","unstructured":"Yuan L, Yang L, Zhang S, et al. 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