{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T05:06:02Z","timestamp":1784005562597,"version":"3.55.0"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Zhejiang Province Postdoctoral Research Excellence Funding Program","award":["ZJ2025048"],"award-info":[{"award-number":["ZJ2025048"]}]},{"name":"Discovery, Adventure, Momentum and Outlook (DAMO) Academy through DAMO Academy Research Intern Program"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1109\/tmi.2026.3686884","type":"journal-article","created":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T19:59:01Z","timestamp":1776974341000},"page":"3824-3834","source":"Crossref","is-referenced-by-count":0,"title":["Clinical Knowledge-Guided PET\/CT Lesion Segmentation With Interpretable Fusion of Metabolic and Structural Cues"],"prefix":"10.1109","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-7499-9816","authenticated-orcid":false,"given":"Song","family":"Zhang","sequence":"first","affiliation":[{"name":"Alibaba Group, DAMO Academy, Alibaba Group, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6516-4012","authenticated-orcid":false,"given":"Jiajin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, DAMO Academy, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liheng","family":"Qiu","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Peking University People&#x2019;s Hospital, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3655-0058","authenticated-orcid":false,"given":"Wei","family":"Liu","sequence":"additional","affiliation":[{"name":"Hupan Laboratory, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4806-2943","authenticated-orcid":false,"given":"Dakai","family":"Jin","sequence":"additional","affiliation":[{"name":"Alibaba Group, DAMO Academy, New York City, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7546-6089","authenticated-orcid":false,"given":"Wenpei","family":"Jiao","sequence":"additional","affiliation":[{"name":"Alibaba Group, DAMO Academy, Alibaba Group, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6799-9416","authenticated-orcid":false,"given":"Le","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Peking University People&#x2019;s Hospital, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6136-0486","authenticated-orcid":false,"given":"Tzu-Chen","family":"Yen","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine and Molecular Imaging Center, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7261-8449","authenticated-orcid":false,"given":"Shenmiao","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Hematology, Peking University People&#x2019;s Hospital, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0034-9013","authenticated-orcid":false,"given":"Ke","family":"Yan","sequence":"additional","affiliation":[{"name":"Alibaba Group, DAMO Academy, Alibaba Group, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2312021185"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1148\/rg.242025724"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-005-1762-7"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.123.265872"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-021-05480-3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.108.054205"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.16.16532"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1002\/cncr.29565"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s10549-015-3558-1"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.119.238923"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.117.193946"},{"key":"ref12","article-title":"Autopet challenge 2023: NnUNet-based whole-body 3D PET-CT tumour segmentation","author":"Alloula","year":"2023","journal-title":"arXiv:2309.13675"},{"key":"ref13","article-title":"Exploring vanilla U-Net for lesion segmentation from whole-body FDG-PET\/CT scans","author":"Ye","year":"2022","journal-title":"arXiv:2210.07490"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2022.3226475"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2021.106043"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1002\/mp.13331"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.106538"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-63211-2_14"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72114-4_39"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1182\/blood-2018-01-826958"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1182\/blood-2017-04-773838"},{"key":"ref22","article-title":"Baseline PET features as predictors of outcome in advanced HL: A prospective evaluation of U.K. patients in the RATHL trial (CRUK\/07\/033)","volume":"2","author":"Guezennec","year":"2018","journal-title":"Hemasphere"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/ac299a"},{"key":"ref24","article-title":"STU-Net: Scalable and transferable medical image segmentation models empowered by large-scale supervised pre-training","author":"Huang","year":"2023","journal-title":"arXiv:2304.06716"},{"key":"ref25","article-title":"On the benefits of early fusion in multimodal representation learning","author":"Barnum","year":"2020","journal-title":"arXiv:2011.07191"},{"key":"ref26","article-title":"Automatic tumor segmentation via false positive reduction network for whole-body multi-modal PET\/CT images","author":"Peng","year":"2022","journal-title":"arXiv:2209.07705"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2020.104042"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2923601"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.110825"},{"key":"ref30","article-title":"A mirror-UNet architecture for PET\/CT lesion segmentation","author":"Habarnau","year":"2023","journal-title":"arXiv:2309.13398"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3089702"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72111-3_30"},{"key":"ref33","article-title":"A comprehensive survey of mixture-of-experts: Algorithms, theory, and applications","author":"Mu","year":"2025","journal-title":"arXiv:2503.07137"},{"key":"ref34","article-title":"Qwen2.5-VL technical report","volume-title":"arXiv:2502.13923","author":"Bai","year":"2025"},{"key":"ref35","article-title":"LLaMA-MoE v2: Exploring sparsity of LLaMA from perspective of mixture-of-experts with post-training","author":"Qu","year":"2024","journal-title":"arXiv:2411.15708"},{"key":"ref36","article-title":"DeepSeek-V3 technical report","volume-title":"arXiv:2412.19437","author":"Liu","year":"2024"},{"key":"ref37","first-page":"8583","article-title":"Scaling vision with sparse mixture of experts","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Riquelme"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.52202\/075280-3049"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.52202\/075280-1806"},{"key":"ref40","article-title":"Customize segment anything model for multi-modal semantic segmentation with mixture of LoRA experts","author":"Zhu","year":"2024","journal-title":"arXiv:2412.04220"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16443-9_46"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-43898-1_54"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1053\/sroe.2001.25126"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/s00261-005-0031-3"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1182\/blood.2022018558"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-020-01008-z"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.230024.podcast"},{"key":"ref48","volume-title":"Autopet III: Tumor Segmentation Using NnUNet With ResNet Encoder","author":"Alasmawi","year":"2024"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/aaf44b"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-43904-9_8"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00181"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-08999-2_22"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-022-01718-3"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102336"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-013-9622-7"},{"key":"ref56","first-page":"1","article-title":"PyTorch: An imperative style, high-performance deep learning library","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Paszke"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00135"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/42\/11606328\/11494071.pdf?arnumber=11494071","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T04:39:55Z","timestamp":1784003995000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11494071\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":57,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2026.3686884","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7]]}}}