{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,11]],"date-time":"2026-01-11T22:49:19Z","timestamp":1768171759260,"version":"3.49.0"},"reference-count":19,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,3,28]],"date-time":"2022-03-28T00:00:00Z","timestamp":1648425600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,3,28]],"date-time":"2022-03-28T00:00:00Z","timestamp":1648425600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,3,28]]},"DOI":"10.1109\/isbi52829.2022.9761538","type":"proceedings-article","created":{"date-parts":[[2022,4,26]],"date-time":"2022-04-26T19:39:34Z","timestamp":1651001974000},"page":"1-5","source":"Crossref","is-referenced-by-count":3,"title":["Multi-Class Brain Tumor Segmentation via 3d and 2d Neural Networks"],"prefix":"10.1109","author":[{"given":"Sergey","family":"Pnev","sequence":"first","affiliation":[{"name":"Novosibirsk State University,Novosibirsk,Russia"}]},{"given":"Vladimir","family":"Groza","sequence":"additional","affiliation":[{"name":"Novosibirsk State University,Novosibirsk,Russia"}]},{"given":"Bair","family":"Tuchinov","sequence":"additional","affiliation":[{"name":"Novosibirsk State University,Novosibirsk,Russia"}]},{"given":"Evgeniya","family":"Amelina","sequence":"additional","affiliation":[{"name":"Novosibirsk State University,Novosibirsk,Russia"}]},{"given":"Evgeniy","family":"Pavlovskiy","sequence":"additional","affiliation":[{"name":"Novosibirsk State University,Novosibirsk,Russia"}]},{"given":"Nikolay","family":"Tolstokulakov","sequence":"additional","affiliation":[{"name":"Novosibirsk State University,Novosibirsk,Russia"}]},{"given":"Mihail","family":"Amelin","sequence":"additional","affiliation":[{"name":"Novosibirsk State University,Novosibirsk,Russia"}]},{"given":"Sergey","family":"Golushko","sequence":"additional","affiliation":[{"name":"Novosibirsk State University,Novosibirsk,Russia"}]},{"given":"Andrey","family":"Letyagin","sequence":"additional","affiliation":[{"name":"Branch of IC&#x0026;G SBRAS,Research Institute of Clinical and Experimental Lymphology,Novosibirsk,Russia"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2377694"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2017.117"},{"key":"ref12","article-title":"Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the brats challenge","author":"bakas","year":"2018"},{"key":"ref13","article-title":"Segmentation labels and radiomic features for the pre-operative scans of the tcga-gbm collection","author":"bakas","year":"2017","journal-title":"The Cancer Imaging Archive"},{"key":"ref14","article-title":"Deep learning using rectified linear units (relu)","author":"agarap","year":"2018"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_22"},{"key":"ref16","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"dosovitskiy","year":"2020"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-45385-5_62"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CSGB51356.2020.9214645"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ISBIWorkshops50223.2020.9153416"},{"key":"ref4","first-page":"231","article-title":"Two-stage cascaded u-net: 1st place solution to brats challenge 2019 segmentation task","author":"jiang","year":"2019","journal-title":"International MICCAI Brain lesion Workshop"},{"key":"ref3","article-title":"3d mri brain tumor segmentation using autoencoder regularization","author":"myronenko","year":"2018"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32248-9_21"},{"key":"ref5","first-page":"118","article-title":"nnu-net for brain tumor segmentation","author":"isensee","year":"2020","journal-title":"International MICCAI Brain lesion Workshop"},{"key":"ref8","article-title":"Transunet: Transformers make strong encoders for medical image segmentation","author":"chen","year":"2021"},{"key":"ref7","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/VCIP.2017.8305148"},{"key":"ref1","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","volume":"9351","author":"ronneberger","year":"2015","journal-title":"MICCAI 2015 LNCS"},{"key":"ref9","first-page":"109","article-title":"Transbts: Multimodal brain tumor segmentation using transformer","author":"wang","year":"2021","journal-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention"}],"event":{"name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","location":"Kolkata, India","start":{"date-parts":[[2022,3,28]]},"end":{"date-parts":[[2022,3,31]]}},"container-title":["2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9761376\/9761399\/09761538.pdf?arnumber=9761538","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T21:06:42Z","timestamp":1656364002000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9761538\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,28]]},"references-count":19,"URL":"https:\/\/doi.org\/10.1109\/isbi52829.2022.9761538","relation":{},"subject":[],"published":{"date-parts":[[2022,3,28]]}}}