{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T15:53:47Z","timestamp":1780502027529,"version":"3.54.1"},"reference-count":43,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"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":["82394432,92249302"],"award-info":[{"award-number":["82394432,92249302"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003347","name":"Fudan University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,19]]},"DOI":"10.1109\/iccv51701.2025.01961","type":"proceedings-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T19:45:49Z","timestamp":1777491949000},"page":"21107-21116","source":"Crossref","is-referenced-by-count":3,"title":["SegAnyPET: Universal Promptable Segmentation from Positron Emission Tomography Images"],"prefix":"10.1109","author":[{"given":"Yichi","family":"Zhang","sequence":"first","affiliation":[{"name":"Fudan University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Le","family":"Xue","sequence":"additional","affiliation":[{"name":"Fudan University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenbo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Fudan University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lanlan","family":"Li","sequence":"additional","affiliation":[{"name":"Fudan University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuchen","family":"Liu","sequence":"additional","affiliation":[{"name":"Fudan University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Jiang","sequence":"additional","affiliation":[{"name":"Shanghai Academy of Artificial Intelligence for Science"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuan","family":"Cheng","sequence":"additional","affiliation":[{"name":"Fudan University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuan","family":"Qi","sequence":"additional","affiliation":[{"name":"Fudan University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","article-title":"M3d: Advancing 3d medical image analysis with multi-modal large language models","author":"Bai","year":"2024","journal-title":"arXiv preprint"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.03.009"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.52202\/079017-3516"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-022-01718-3"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2024.103324"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-08999-2_22"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.103061"},{"key":"ref8","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 preprint"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-020-01008-z"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.52202\/068431-2661"},{"key":"ref11","first-page":"4904","article-title":"Scaling up visual and vision-language representation learning with noisy text supervision","volume-title":"International Conference on Machine Learning","author":"Jia"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.107840"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.21172\/1.84.31"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2024.103370"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-99-8141-0_11"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2017.07.005"},{"key":"ref18","first-page":"1304","article-title":"Lynch and Conor Liston","volume":"24","author":"Charles","year":"2018","journal-title":"New machinelearning technologies for computer-aided diagnosis. Nature Medicine"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3100536"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-44824-z"},{"key":"ref21","article-title":"Segment anything in medical images and videos: Benchmark and deployment","author":"Ma","year":"2024","journal-title":"arXiv preprint"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102918"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-05881-4"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11726-9_28"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102336"},{"key":"ref26","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","volume-title":"International conference on machine learning","author":"Radford"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TRPMS.2019.2926889"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1038\/s41568-023-00576-4"},{"key":"ref30","article-title":"Beyond pixel-wise supervision for medical image segmentation: From traditional models to foundation models","author":"Shi","year":"2024","journal-title":"arXiv preprint"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-022-05832-7"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-91721-9_4"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-025-07156-8"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.230024.podcast"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.210284"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-73661-2_12"},{"key":"ref37","article-title":"Sa-med2d-20m dataset: Segment anything in 2d medical imaging with 20 million masks","author":"Ye","year":"2023","journal-title":"arXiv preprint"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102996"},{"key":"ref39","article-title":"Segment anything model with uncertainty rectification for auto-prompting medical image segmentation","author":"Zhang","year":"2023","journal-title":"arXiv preprint"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2022.102476"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2024.108238"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/BIBM62325.2024.10821951"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2016.07.045"}],"event":{"name":"2025 IEEE\/CVF International Conference on Computer Vision (ICCV)","location":"Honolulu, HI, USA","start":{"date-parts":[[2025,10,19]]},"end":{"date-parts":[[2025,10,25]]}},"container-title":["2025 IEEE\/CVF International Conference on Computer Vision (ICCV)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11443115\/11443287\/11445085.pdf?arnumber=11445085","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T06:13:01Z","timestamp":1777529581000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11445085\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,19]]},"references-count":43,"URL":"https:\/\/doi.org\/10.1109\/iccv51701.2025.01961","relation":{},"subject":[],"published":{"date-parts":[[2025,10,19]]}}}