{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T09:53:16Z","timestamp":1787997196201,"version":"build-2784847793"},"reference-count":21,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2018,9,1]],"date-time":"2018-09-01T00:00:00Z","timestamp":1535760000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"DOI":"10.13039\/501100000781","name":"European Research Council","doi-asserted-by":"publisher","award":["MedYMA ERC-AdG-2011-291080"],"award-info":[{"award-number":["MedYMA ERC-AdG-2011-291080"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1109\/tmi.2018.2820742","type":"journal-article","created":{"date-parts":[[2018,3,29]],"date-time":"2018-03-29T18:06:05Z","timestamp":1522346765000},"page":"2137-2148","source":"Crossref","is-referenced-by-count":165,"title":["3-D Consistent and Robust Segmentation of Cardiac Images by Deep Learning With Spatial Propagation"],"prefix":"10.1109","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5713-3870","authenticated-orcid":false,"given":"Qiao","family":"Zheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Herve","family":"Delingette","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8803-2004","authenticated-orcid":false,"given":"Nicolas","family":"Duchateau","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicholas","family":"Ayache","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","article-title":"Evaluation framework for algorithms segmenting short axis cardiac MRI","author":"radau","year":"2009","journal-title":"MIDAS J &#x2014;Cardiac MR Left Ventricle Segmentation Challenge"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2014.10.004"},{"key":"ref12","first-page":"1167","article-title":"Standardized image interpretation and post processing in cardiovascular magnetic resonance: Society for cardiovascular magnetic resonance (SCMR) board of trustees task force on standardized post processing","volume":"15","author":"schulz-menger","year":"2013","journal-title":"J Cardiovascular Magn Reson"},{"key":"ref13","first-page":"1","article-title":"Rectifier nonlinearities improve neural network acoustic models","volume":"30","author":"maas","year":"2013","journal-title":"Proc ICML"},{"key":"ref14","author":"kayalibay","year":"2017","journal-title":"Cnn-based segmentation of medical imaging data"},{"key":"ref15","first-page":"1","article-title":"Automatic segmentation and disease classification using cardiac cine MR images","author":"wolterink","year":"2017","journal-title":"Proc Statist Atlases Comput Models Heart (STACOM) ACDC Challenge MICCAI Workshop"},{"key":"ref16","author":"bai","year":"2017","journal-title":"Human-level cmr image analysis with deep fully convolutional networks"},{"key":"ref17","first-page":"161","article-title":"Automatic segmentation of LV and RV in cardiac MRI","author":"jang","year":"2017","journal-title":"Proc Statist Atlases Comput Models Heart (STACOM) ACDC Challenge MICCAI Workshop"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.01.005"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2014.06.001"},{"key":"ref4","first-page":"111","article-title":"An exploration of 2D and 3D deep learning techniques for cardiac MR image segmentation","author":"baumgartner","year":"2017","journal-title":"Proc Statist Atlases Comput Models Heart (STACOM) ACDC Challenge MICCAI Workshop"},{"key":"ref3","author":"tran","year":"2016","journal-title":"A Fully Convolutional Neural Network for Cardiac Segmentation in Short-Axis MRI arXiv"},{"key":"ref6","author":"poudel","year":"2016","journal-title":"Recurrent fully convolutional neural networks for multi-slice MRI cardiac segmentation"},{"key":"ref5","first-page":"120","article-title":"Automatic cardiac disease assessment on cine-MRI via time-series segmentation and domain specific features","author":"isensee","year":"2017","journal-title":"Proc Statist Atlases Comput Models Heart (STACOM) ACDC Challenge MICCAI Workshop"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1186\/s12968-015-0170-9"},{"key":"ref7","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","volume":"9351","author":"ronneberger","year":"2015","journal-title":"Proc MICCAI"},{"key":"ref2","author":"winther","year":"2017","journal-title":"$\\nu $ -net Deep learning for generalized biventricular cardiac mass and function parameters"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1186\/s12968-016-0227-4"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2743464"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"351p","DOI":"10.1186\/1532-429X-18-S1-P351","article-title":"Fully automatic segmentation of heart chambers in cardiac MRI using deep learning","volume":"18","author":"avendi","year":"2016","journal-title":"J Cardiovascular Magn Reson"},{"key":"ref21","first-page":"172","article-title":"Multi-atlas propagation whole heart segmentation from MRI and CTA using a local normalised correlation coefficient criterion","volume":"7945","author":"zuluaga","year":"2013","journal-title":"Functional Imaging and Modeling of the Heart"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/8452189\/08327905.pdf?arnumber=8327905","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T14:06:39Z","timestamp":1643205999000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8327905\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9]]},"references-count":21,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2018.2820742","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,9]]}}}