{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T18:19:01Z","timestamp":1793297941209,"version":"4.5.0"},"reference-count":34,"publisher":"World Scientific Pub Co Pte Ltd","issue":"07","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62376176"],"award-info":[{"award-number":["62376176"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Science and Technology Department of Sichuan Province","award":["2023YFG0272"],"award-info":[{"award-number":["2023YFG0272"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Neur. Syst."],"published-print":{"date-parts":[[2024,7]]},"abstract":"<jats:p>Surgical reconstruction of mandibular defects is a clinical routine manner for the rehabilitation of patients with deformities. The mandible plays a crucial role in maintaining the facial contour and ensuring the speech and mastication functions. The repairing and reconstruction of mandible defects is a significant yet challenging task in oral\u2013maxillofacial surgery. Currently, the mainly available methods are traditional digitalized design methods that suffer from substantial artificial operations, limited applicability and high reconstruction error rates. An automated, precise, and individualized method is imperative for maxillofacial surgeons. In this paper, we propose a Stage-wise Residual Attention Generative Adversarial Network (SRA-GAN) for mandibular defect reconstruction. Specifically, we design a stage-wise residual attention mechanism for generator to enhance the extraction capability of mandibular remote spatial information, making it adaptable to various defects. For the discriminator, we propose a multi-field perceptual network, consisting of two parallel discriminators with different perceptual fields, to reduce the cumulative reconstruction errors. Furthermore, we design a self-encoder perceptual loss function to ensure the correctness of mandibular anatomical structures. The experimental results on a novel custom-built mandibular defect dataset demonstrate that our method has a promising prospect in clinical application, achieving the best Dice Similarity Coefficient (DSC) of 94.238% and 95% Hausdorff Distance (HD95) of 4.787.<\/jats:p>","DOI":"10.1142\/s0129065724500333","type":"journal-article","created":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T05:42:56Z","timestamp":1711086176000},"source":"Crossref","is-referenced-by-count":19,"title":["A Stage-Wise Residual Attention Generation Adversarial Network for Mandibular Defect Repairing and Reconstruction"],"prefix":"10.1142","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-4159-4760","authenticated-orcid":false,"given":"Chenglan","family":"Zhong","sequence":"first","affiliation":[{"name":"Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu 610065, P.\u00a0R.\u00a0China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1257-4055","authenticated-orcid":false,"given":"Yutao","family":"Xiong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, P.\u00a0R.\u00a0China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7568-2884","authenticated-orcid":false,"given":"Wei","family":"Tang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, P.\u00a0R.\u00a0China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1678-8205","authenticated-orcid":false,"given":"Jixiang","family":"Guo","sequence":"additional","affiliation":[{"name":"Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu 610065, P.\u00a0R.\u00a0China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"219","published-online":{"date-parts":[[2024,4,13]]},"reference":[{"key":"S0129065724500333BIB001","doi-asserted-by":"publisher","DOI":"10.1016\/j.msec.2019.109858"},{"key":"S0129065724500333BIB002","doi-asserted-by":"publisher","DOI":"10.1186\/s40902-018-0141-9"},{"key":"S0129065724500333BIB003","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcms.2019.11.024"},{"key":"S0129065724500333BIB004","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2016.7590915"},{"key":"S0129065724500333BIB005","doi-asserted-by":"publisher","DOI":"10.1007\/s10006-018-0704-z"},{"key":"S0129065724500333BIB006","doi-asserted-by":"publisher","DOI":"10.1016\/j.joms.2022.07.041"},{"key":"S0129065724500333BIB007","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3077047"},{"key":"S0129065724500333BIB008","doi-asserted-by":"publisher","DOI":"10.1002\/int.23006"},{"key":"S0129065724500333BIB009","doi-asserted-by":"publisher","DOI":"10.3390\/math8081246"},{"key":"S0129065724500333BIB010","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmapro.2015.11.006"},{"key":"S0129065724500333BIB011","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-017-0808-2"},{"key":"S0129065724500333BIB012","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcms.2019.03.027"},{"key":"S0129065724500333BIB013","doi-asserted-by":"publisher","DOI":"10.1016\/j.joms.2018.10.023"},{"key":"S0129065724500333BIB014","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-017-1674-6"},{"key":"S0129065724500333BIB015","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065723500077"},{"key":"S0129065724500333BIB016","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065723500144"},{"key":"S0129065724500333BIB017","doi-asserted-by":"publisher","DOI":"10.1142\/S012906572150026X"},{"key":"S0129065724500333BIB018","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-16187-3_15"},{"key":"S0129065724500333BIB019","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-92652-6"},{"key":"S0129065724500333BIB021","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-64327-0_6"},{"key":"S0129065724500333BIB022","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-64327-0_3"},{"key":"S0129065724500333BIB023","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-92652-6_8"},{"key":"S0129065724500333BIB024","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-92652-6_10"},{"key":"S0129065724500333BIB025","first-page":"10","volume":"27","author":"Goodfellow I.","year":"2014","journal-title":"Adv. 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