{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T10:36:09Z","timestamp":1763202969144,"version":"3.28.0"},"reference-count":26,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,6,30]],"date-time":"2024-06-30T00:00:00Z","timestamp":1719705600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,6,30]],"date-time":"2024-06-30T00:00:00Z","timestamp":1719705600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100006190","name":"Research and Development","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006190","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,6,30]]},"DOI":"10.1109\/ijcnn60899.2024.10650077","type":"proceedings-article","created":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T17:35:05Z","timestamp":1725903305000},"page":"1-7","source":"Crossref","is-referenced-by-count":1,"title":["Automatic Segmentation of Organs-At-Risk and Clinical Target Volume for Cervical Cancer Using Manifold Learning"],"prefix":"10.1109","author":[{"given":"Chenyu","family":"Zuo","sequence":"first","affiliation":[{"name":"Beijing University of Posts and Telecommunications,Key Laboratory of Universal Wireless Communications, Ministry of Education,Beijing,China"}]},{"given":"Runhong","family":"Lei","sequence":"additional","affiliation":[{"name":"Peking University Third Hospital,Cancer Center,Department of Radiation Oncology,Beijing,China"}]},{"given":"Xi","family":"Liu","sequence":"additional","affiliation":[{"name":"Peking University Third Hospital,Cancer Center,Department of Radiation Oncology,Beijing,China"}]},{"given":"Kai","family":"Niu","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications,Key Laboratory of Universal Wireless Communications, Ministry of Education,Beijing,China"}]},{"given":"Zhiqiang","family":"He","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications,Key Laboratory of Universal Wireless Communications, Ministry of Education,Beijing,China"}]},{"given":"Ruijie","family":"Yang","sequence":"additional","affiliation":[{"name":"Peking University Third Hospital,Cancer Center,Department of Radiation Oncology,Beijing,China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/S2214-109X(22)00501-0"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/mp.16135"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.106501"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.118625"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102642"},{"journal-title":"The mathematical foundations of manifold learning","year":"2020","author":"Melas-Kyriazi","key":"ref6"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2021.717039"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1093\/jrr\/rraa094"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1002\/mp.15862"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejmp.2019.12.008"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2867837"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1177\/15330338221139164"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1002\/mp.14898"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2013.03.006"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-019-02097-8"},{"issue":"1-17","key":"ref16","first-page":"1","article-title":"Algorithms for manifold learning","volume":"12","author":"Cayton","year":"2005","journal-title":"Univ. of California at San Diego Tech. Rep"},{"journal-title":"The intrinsic dimension of images and its impact on learning","year":"2021","author":"Pope","key":"ref17"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11768"},{"key":"ref19","article-title":"Can we gain more from orthogonality regularizations in training deep networks?","volume":"31","author":"Bansal","year":"2018","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1515\/9781400830244"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s40305-020-00295-9"},{"journal-title":"Mctorch, a manifold optimization library for deep learning","year":"2018","author":"Meghwanshi","key":"ref22"},{"journal-title":"Pymanopt: A python toolbox for optimization on manifolds using automatic differentiation","year":"2016","author":"Townsend","key":"ref23"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1137\/100802529"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-020-01008-z"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/122"}],"event":{"name":"2024 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2024,6,30]]},"location":"Yokohama, Japan","end":{"date-parts":[[2024,7,5]]}},"container-title":["2024 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10649807\/10649898\/10650077.pdf?arnumber=10650077","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T07:12:00Z","timestamp":1725952320000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10650077\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,30]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/ijcnn60899.2024.10650077","relation":{},"subject":[],"published":{"date-parts":[[2024,6,30]]}}}