{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,5]],"date-time":"2025-06-05T04:53:23Z","timestamp":1749099203085,"version":"3.37.3"},"reference-count":51,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62001464"],"award-info":[{"award-number":["62001464"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangzhou Key Research and Development","award":["202206080008"],"award-info":[{"award-number":["202206080008"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2023,2]]},"DOI":"10.1109\/tmi.2022.3212784","type":"journal-article","created":{"date-parts":[[2022,10,6]],"date-time":"2022-10-06T19:36:49Z","timestamp":1665085009000},"page":"507-518","source":"Crossref","is-referenced-by-count":7,"title":["GraphSKT: Graph-Guided Structured Knowledge Transfer for Domain Adaptive Lesion Detection"],"prefix":"10.1109","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0052-3819","authenticated-orcid":false,"given":"Chaoqi","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Computer Science, The University of Hong Kong, Hong Kong, SAR, China"}]},{"given":"Jiexiang","family":"Wang","sequence":"additional","affiliation":[{"name":"ByteDance, Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8781-6090","authenticated-orcid":false,"given":"Junwen","family":"Pan","sequence":"additional","affiliation":[{"name":"ByteDance, Guangzhou, China"}]},{"given":"Cheng","family":"Bian","sequence":"additional","affiliation":[{"name":"ByteDance, Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5333-1394","authenticated-orcid":false,"given":"Zhicheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"ByteDance, Guangzhou, China"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01237"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00889"},{"key":"ref15","first-page":"2664","article-title":"Gromov-Wasserstein averaging of kernel and distance matrices","author":"peyr\u00e9","year":"2016","journal-title":"Proc 33rd Int Conf Mach Learn"},{"key":"ref14","first-page":"740","article-title":"Microsoft COCO: Common objects in context","author":"lin","year":"2014","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00677"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01172"},{"key":"ref17","first-page":"1","article-title":"Central moment discrepancy (CMD) for domain-invariant representation learning","author":"zellinger","year":"2017","journal-title":"Proc ICLR"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-49409-8_35"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref18","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Proc NIPS"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00921"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01174"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2011.09.014"},{"key":"ref45","first-page":"27","article-title":"The digital database for screening mammography","volume":"58","author":"bowyer","year":"1996","journal-title":"3rd Int Workshop on Digital Mammography"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9413132"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32226-7_53"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-013-0926-3"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2015.02.007"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3356073"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3083187.3083216"},{"key":"ref49","article-title":"SCL: Towards accurate domain adaptive object detection via gradient detach based stacked complementary losses","author":"shen","year":"2019","journal-title":"arXiv 1911 02559"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00078"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00352"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00712"},{"key":"ref4","first-page":"2030","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"ganin","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref3","first-page":"97","article-title":"Learning transferable features with deep adaptation networks","author":"long","year":"2015","journal-title":"Proc 32nd Int Conf Mach Learn"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2021.3117407"},{"key":"ref5","first-page":"2208","article-title":"Deep transfer learning with joint adaptation networks","author":"long","year":"2017","journal-title":"Proc ICML"},{"key":"ref40","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2017","journal-title":"Proc ICLR"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102052"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9562100"},{"key":"ref37","first-page":"1640","article-title":"Conditional adversarial domain adaptation","author":"long","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref36","first-page":"583","article-title":"Random feature maps for dot product kernels","author":"kar","year":"2012","journal-title":"Proc 15th Int Conf Artif Intell Statist"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00408"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2832217"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3128560"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1055\/s-0040-1702009"},{"key":"ref2","article-title":"Deep domain confusion: Maximizing for domain invariance","author":"tzeng","year":"2014","journal-title":"arXiv 1412 3474"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995347"},{"key":"ref39","first-page":"6932","article-title":"Gromov-Wasserstein learning for graph matching and node embedding","author":"xu","year":"2019","journal-title":"Proc 36th Int Conf Mach Learn"},{"key":"ref38","first-page":"1","article-title":"Graph attention networks","author":"veli?kovi?","year":"2018","journal-title":"Proc ICLR"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00677"},{"key":"ref23","first-page":"91","article-title":"Faster R-CNN: Towards real-time object detection with region proposal networks","author":"ren","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-59050-9_47"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00270"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00392"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00072"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11767"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00963"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/96"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2870343"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/10035777\/09913486.pdf?arnumber=9913486","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T18:50:03Z","timestamp":1677523803000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9913486\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2]]},"references-count":51,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2022.3212784","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"type":"print","value":"0278-0062"},{"type":"electronic","value":"1558-254X"}],"subject":[],"published":{"date-parts":[[2023,2]]}}}