{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T12:56:40Z","timestamp":1781873800620,"version":"3.54.5"},"reference-count":30,"publisher":"IOP Publishing","issue":"12","license":[{"start":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T00:00:00Z","timestamp":1781827200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T00:00:00Z","timestamp":1781827200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"crossref","award":["2242024k30035"],"award-info":[{"award-number":["2242024k30035"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62171125"],"award-info":[{"award-number":["62171125"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National Key Research and Development Program of China","award":["2025YFE0150500"],"award-info":[{"award-number":["2025YFE0150500"]}]},{"DOI":"10.13039\/501100002949","name":"Jiangsu Province","doi-asserted-by":"crossref","award":["BY2022564"],"award-info":[{"award-number":["BY2022564"]}],"id":[{"id":"10.13039\/501100002949","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2026,6,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Objective.<\/jats:italic>\n                    Accurate prediction of postoperative facial appearance is essential for orthognathic surgical planning, yet remains challenging due to the nonlinear biomechanical coupling between bone and soft tissue. While deep learning methods offer a faster alternative to traditional biomechanical simulation, they typically map bony displacements directly to facial surface deformation, overlooking the intervening soft-tissue layers with distinct biomechanical properties through which displacement is progressively transmitted. Moreover, the many-to-one effect of regional bony movements on each soft-tissue point remains insufficiently captured.\n                    <jats:italic>Approach.<\/jats:italic>\n                    We propose a novel network that introduces an interlayer mixture-of-experts mechanism to decouple bone-to-surface deformation propagation into three biomechanically inspired proxy representations at different tissue depth levels. Since the contribution of each depth level varies across individuals and facial regions, a gated routing network adaptively weights each layer\u2019s contribution, providing a data-driven approximation of spatially heterogeneous, patient-specific deformation transmission. Additionally, a bio-geometric convolution module captures regional bony influences through elastic-weighted neighborhood aggregation.\n                    <jats:italic>Main results.<\/jats:italic>\n                    Evaluations on 88 orthognathic surgery patients demonstrate that the proposed method achieves a mean whole-face error of 1.39 mm, below the 2 mm clinical threshold, with statistically significant improvements over all baselines (\n                    <jats:inline-formula>\n                      <jats:tex-math>\n                        \n                      <\/jats:tex-math>\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" overflow=\"scroll\">\n                        <mml:mrow>\n                          <mml:mi>p<\/mml:mi>\n                          <mml:mo>&lt;<\/mml:mo>\n                          <mml:mn>0.05<\/mml:mn>\n                        <\/mml:mrow>\n                      <\/mml:math>\n                    <\/jats:inline-formula>\n                    ) and the highest clinician acceptance rate (94%).\n                    <jats:italic>Significance.<\/jats:italic>\n                    By incorporating bio-geometric priors into a deep learning framework, our approach enables a more physically grounded and interpretable prediction paradigm, supporting efficient and clinically reliable surgical planning.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/ae752e","type":"journal-article","created":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T22:54:36Z","timestamp":1780095276000},"page":"125013","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Interlayer-aware postoperative facial appearance prediction in orthognathic surgery with bio-geometric 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Applications (Southeast University)"},{"name":"Southeast University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9434-6341","authenticated-orcid":false,"given":"Lotfi","family":"Senhadji","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Rennes, INSERM, LTSI-UMR 1099"},{"name":"Centre de Recherche en Information Biom\u00e9dicale Sino-Fran\u00e7ais (CRIBs)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3833-7915","authenticated-orcid":true,"given":"Huazhong","family":"Shu","sequence":"additional","affiliation":[{"name":"LIST, Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University)"},{"name":"Southeast University"},{"name":"Centre de Recherche en Information Biom\u00e9dicale Sino-Fran\u00e7ais (CRIBs)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7171-1318","authenticated-orcid":true,"given":"Jiasong","family":"Wu","sequence":"additional","affiliation":[{"name":"LIST, Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University)"},{"name":"Southeast University"},{"name":"Centre de Recherche en Information Biom\u00e9dicale Sino-Fran\u00e7ais (CRIBs)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luwei","family":"Liu","sequence":"additional","affiliation":[{"name":"The Affiliated Stomatological Hospital of Nanjing Medical University"},{"name":"Prevention and Treatment for Oral Diseases (Nanjing Medical University)"},{"name":"Jiangsu Province Engineering Research Center of Stomatological Translational Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Yan","sequence":"additional","affiliation":[{"name":"The 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2026-03-19","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-05-29","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-06-19","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}