{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T03:04:09Z","timestamp":1772507049195,"version":"3.50.1"},"reference-count":15,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T00:00:00Z","timestamp":1618272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T00:00:00Z","timestamp":1618272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T00:00:00Z","timestamp":1618272000000},"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":[[2021,4,13]]},"DOI":"10.1109\/isbi48211.2021.9434070","type":"proceedings-article","created":{"date-parts":[[2021,5,25]],"date-time":"2021-05-25T20:14:15Z","timestamp":1621973655000},"page":"1164-1168","source":"Crossref","is-referenced-by-count":3,"title":["Brain Surface Reconstruction from MRI Images based on Segmentation Networks Applying Signed Distance Maps"],"prefix":"10.1109","author":[{"given":"Heng","family":"Fang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xi","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Taichi","family":"Kin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Takeo","family":"Igarashi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2930068"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32692-0_71"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00389"},{"key":"ref13","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":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6946"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123425"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2004.03.032"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-23626-6_78"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.3390\/app9030569"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.04.041"},{"key":"ref8","article-title":"How distance transform maps boost segmentation cnns: An empirical study","author":"ma","year":"2020","journal-title":"Medical Imaging with Deep Learning (MIDL)"},{"key":"ref7","article-title":"Imagenet-trained cnns are biased towards texture; increasing shape bias improves accuracy and robustness","author":"geirhos","year":"2018","journal-title":"arXiv preprint arXiv 1811 12231"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/app10051773"},{"key":"ref1","first-page":"1","article-title":"Stateof-the-art traditional to the machine-and deep-learning-based skull stripping techniques, models, and algorithms","author":"fatima","year":"2020","journal-title":"Journal of Digital Imaging"},{"key":"ref9","first-page":"285","article-title":"Boundary loss for highly unbalanced segmentation","author":"kervadec","year":"2019","journal-title":"International Conference on Medical Imaging with Deep Learning"}],"event":{"name":"2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)","location":"Nice, France","start":{"date-parts":[[2021,4,13]]},"end":{"date-parts":[[2021,4,16]]}},"container-title":["2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9433749\/9433753\/09434070.pdf?arnumber=9434070","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:41:34Z","timestamp":1652197294000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9434070\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,13]]},"references-count":15,"URL":"https:\/\/doi.org\/10.1109\/isbi48211.2021.9434070","relation":{},"subject":[],"published":{"date-parts":[[2021,4,13]]}}}