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Existing solutions often rely on enclosed, dedicated acquisition instruments with nontrivial operation, whereas mobile self-capture approaches are more accessible but sensitive to environmental variability, making reliable analysis challenging in real-world use.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To develop a portable non-contact tongue imaging and automated analysis system that is robust to real-world acquisition variability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We designed a portable acquisition terminal that integrates a camera, touchscreen preview, touch-initiated capture with voice prompts, and supplementary illumination for acquisition assistance. For automated analysis, we developed TongueSegNet (TSegNet) for tongue segmentation, incorporating stage-dependent residual modulation, deep-stage attention enhancement, and gated skip-pathway feature fusion to improve feature representation and boundary delineation. For fissured-tongue feature recognition, we developed Residual Kolmogorov-Arnold Network (ResKAN), which combines a convolutional neural network feature extractor with a Kolmogorov-Arnold Network\u2013based head to improve modelling capacity for fine-grained texture patterns.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>On tongue images acquired under unconstrained conditions, TSegNet achieved mean Dice of 98.16%, mean intersection over union of 96.42%, and mean pixel accuracy of 98.31%, outperforming representative baselines. ResKAN achieved mean accuracy of 92.48%, sensitivity of 92.67%, specificity of 92.31%, and a fissured-class F1 score of 92.34%.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The proposed system enables reliable non-contact tongue imaging with automated server-side analysis under unconstrained conditions. These findings support the feasibility of this integrated approach as an initial step toward more accessible automated tongue-image analysis in community and home settings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/20552076261455223","type":"journal-article","created":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T20:36:44Z","timestamp":1782333404000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["A portable non-contact tongue imaging system with automated analysis for community and home settings"],"prefix":"10.1177","volume":"12","author":[{"given":"Jiehan","family":"Wei","sequence":"first","affiliation":[{"name":"Guangdong Polytechnic Normal University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Song","sequence":"additional","affiliation":[{"name":"Guangdong Polytechnic Normal University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiliang","family":"Lu","sequence":"additional","affiliation":[{"name":"Guangdong Polytechnic Normal University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaoyang","family":"Men","sequence":"additional","affiliation":[{"name":"Guangzhou University of Chinese Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuangquan","family":"Lin","sequence":"additional","affiliation":[{"name":"Guangzhou University of Chinese Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peipei","family":"Zhou","sequence":"additional","affiliation":[{"name":"Guangdong Polytechnic Normal University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,6,24]]},"reference":[{"key":"e_1_3_5_2_2","doi-asserted-by":"publisher","DOI":"10.3934\/mbe.2021063"},{"key":"e_1_3_5_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13167-021-00253-2"},{"key":"e_1_3_5_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11655-013-1350-9"},{"key":"e_1_3_5_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcma.2018.01.005"},{"key":"e_1_3_5_6_2","doi-asserted-by":"publisher","DOI":"10.2147\/PPA.S398644"},{"key":"e_1_3_5_7_2","doi-asserted-by":"publisher","DOI":"10.1177\/20552076231191044"},{"key":"e_1_3_5_8_2","doi-asserted-by":"crossref","unstructured":"Zhou H Hu G Zhang X. constitution identification of tongue image based on CNN. 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