{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T00:24:06Z","timestamp":1769300646162,"version":"3.49.0"},"reference-count":11,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,12,9]],"date-time":"2021-12-09T00:00:00Z","timestamp":1639008000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,9]],"date-time":"2021-12-09T00:00:00Z","timestamp":1639008000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,9]],"date-time":"2021-12-09T00:00:00Z","timestamp":1639008000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"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":[[2021,12,9]]},"DOI":"10.1109\/bibm52615.2021.9669799","type":"proceedings-article","created":{"date-parts":[[2022,1,14]],"date-time":"2022-01-14T20:40:30Z","timestamp":1642192830000},"page":"1542-1545","source":"Crossref","is-referenced-by-count":5,"title":["Multi-scale Hierarchical Transformer structure for 3D medical image segmentation"],"prefix":"10.1109","author":[{"given":"Luyao","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bangze","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojie","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cong","family":"Bai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"Xia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peiliang","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref4","first-page":"424","article-title":"3d u-net: learning dense volumetric segmentation from sparse annotation","author":"\u00e7i\u00e7ek","year":"2016","journal-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention"},{"key":"ref3","article-title":"Transunet: Transformers make strong encoders for medical image segmentation","author":"chen","year":"2021","journal-title":"arXiv preprint arXiv 2102 05988"},{"key":"ref10","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref6","article-title":"Cmt: Convolutional neural networks meet vision transformers","author":"guo","year":"2021","journal-title":"arXiv preprint arXiv 2107 06263"},{"key":"ref11","article-title":"Pyramid vision transformer: A versatile backbone for dense prediction without convolutions","author":"wang","year":"2021","journal-title":"arXiv preprint arXiv 2102 12041"},{"key":"ref5","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"dosovitskiy","year":"2020","journal-title":"arXiv preprint arXiv 2010 10042"},{"key":"ref8","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention"},{"key":"ref7","article-title":"The kits19 challenge data: 300 kidney tumor cases with clinical context, ct semantic segmentations, and surgical outcomes","author":"heller","year":"2019","journal-title":"arXiv preprint arXiv 1904 01870"},{"key":"ref2","first-page":"213","article-title":"End-to-end object detection with transformers","author":"carion","year":"2020","journal-title":"in European Conference on Computer Vision"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59719-1_36"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"}],"event":{"name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","location":"Houston, TX, USA","start":{"date-parts":[[2021,12,9]]},"end":{"date-parts":[[2021,12,12]]}},"container-title":["2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9669261\/9669139\/09669799.pdf?arnumber=9669799","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T16:57:12Z","timestamp":1652201832000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9669799\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,9]]},"references-count":11,"URL":"https:\/\/doi.org\/10.1109\/bibm52615.2021.9669799","relation":{},"subject":[],"published":{"date-parts":[[2021,12,9]]}}}