{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T13:19:20Z","timestamp":1760015960472,"version":"3.37.3"},"reference-count":30,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2018,8,1]],"date-time":"2018-08-01T00:00:00Z","timestamp":1533081600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"DOI":"10.13039\/501100002920","name":"Hong Kong Research Grants Council","doi-asserted-by":"publisher","award":["16203115","16245016"],"award-info":[{"award-number":["16203115","16245016"]}],"id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2018,8]]},"DOI":"10.1109\/tip.2018.2829263","type":"journal-article","created":{"date-parts":[[2018,4,23]],"date-time":"2018-04-23T18:36:07Z","timestamp":1524508567000},"page":"3883-3892","source":"Crossref","is-referenced-by-count":3,"title":["3D Randomized Connection Network With Graph-Based Label Inference"],"prefix":"10.1109","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3885-125X","authenticated-orcid":false,"given":"Siqi","family":"Bao","sequence":"first","affiliation":[]},{"given":"Pei","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Tony C. W.","family":"Mok","sequence":"additional","affiliation":[]},{"given":"Albert C. S.","family":"Chung","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"journal-title":"Fully-Connected (DENSE) 3D CRF for Processing Biomedical Scans","year":"2017","key":"ref30"},{"key":"ref10","article-title":"OverFeat: Integrated recognition, localization and detection using convolutional networks","author":"sermanet","year":"2014","journal-title":"Proc ICLR"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"journal-title":"Semantic image segmentation with deep convolutional nets and fully connected crfs","year":"2014","author":"chen","key":"ref12"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.59"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.510"},{"key":"ref15","first-page":"109","article-title":"Efficient inference in fully connected CRFs with Gaussian edge potentials","author":"kr\u00e4henb\u00fchl","year":"2011","journal-title":"Proc Adv Neu Inf Proc Sys"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.392"},{"key":"ref17","first-page":"802","article-title":"Convolutional lstm network: A machine learning approach for precipitation nowcasting","author":"xingjian","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"journal-title":"Spatio-temporal video autoencoder with differentiable memory","year":"2015","author":"patraucean","key":"ref18"},{"key":"ref19","first-page":"807","article-title":"Rectified linear units improve restricted boltzmann machines","author":"nair","year":"2010","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/S1361-8415(02)00054-3"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.07.009"},{"key":"ref3","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"journal-title":"Surpassing Human-level Face Verification Performance on Lfw with Gaussianface","year":"2014","author":"lu","key":"ref6"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.01.021"},{"journal-title":"Very Deep Convolutional Networks for Large-scale Image Recognition","year":"2014","author":"simonyan","key":"ref5"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.231"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"journal-title":"Stroke Facts","year":"2017","key":"ref2"},{"key":"ref9","first-page":"82","article-title":"Recurrent convolutional neural networks for scene labeling","author":"pinheiro","year":"2014","journal-title":"Proc Int Conf Mach Learn"},{"journal-title":"2017 Alzheimer's disease facts and figures","year":"2017","key":"ref1"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/72.279181"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref24","first-page":"550","article-title":"Residual networks behave like ensembles of relatively shallow networks","author":"veit","year":"2016","journal-title":"Proc Adv Neural Inf Syst"},{"key":"ref23","first-page":"424","article-title":"3D U-Net: Learning dense volumetric segmentation from sparse annotation","author":"\u00e7i\u00e7ek","year":"2016","journal-title":"Proc Int Conf Med Image Comput Comput -Assist Intervent"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.233"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2007.09.031"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/8347140\/08345227.pdf?arnumber=8345227","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T16:13:21Z","timestamp":1642004001000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8345227\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8]]},"references-count":30,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tip.2018.2829263","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"type":"print","value":"1057-7149"},{"type":"electronic","value":"1941-0042"}],"subject":[],"published":{"date-parts":[[2018,8]]}}}