{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,3]],"date-time":"2025-04-03T16:23:45Z","timestamp":1743697425981,"version":"3.37.3"},"reference-count":46,"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":[{"name":"National Key R&D Program of China","award":["2017YFC0113000"]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61571165","61572152"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Biomed. Eng."],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1109\/tbme.2017.2762762","type":"journal-article","created":{"date-parts":[[2017,10,13]],"date-time":"2017-10-13T18:37:22Z","timestamp":1507919842000},"page":"1924-1934","source":"Crossref","is-referenced-by-count":59,"title":["Multi-Views Fusion CNN for Left Ventricular Volumes Estimation on Cardiac MR Images"],"prefix":"10.1109","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3662-0335","authenticated-orcid":false,"given":"Gongning","family":"Luo","sequence":"first","affiliation":[]},{"given":"Suyu","family":"Dong","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1347-3491","authenticated-orcid":false,"given":"Kuanquan","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3330-783X","authenticated-orcid":false,"given":"Wangmeng","family":"Zuo","sequence":"additional","affiliation":[]},{"given":"Shaodong","family":"Cao","sequence":"additional","affiliation":[]},{"given":"Henggui","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"journal-title":"Keras","year":"2015","author":"chollet","key":"ref39"},{"key":"ref38","first-page":"630","article-title":"Identity mappings in deep residual networks","author":"he","year":"0","journal-title":"Proc Eur Conf Comput Vision"},{"key":"ref33","first-page":"586","article-title":"Direct estimation of cardiac Bi-ventricular\n volumes with regression forests","volume":"8674","author":"zhen","year":"0","journal-title":"Proc Int Conf Med Image Comput Comput -Assisted Intervention"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2013.2287793"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2014.2299433"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-013-9573-z"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref36","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"0","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"journal-title":"Data Science Bowl Cardiac Challenge Data","year":"2016","key":"ref34"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.21586"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-006-7936-3"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2006.03.009"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2006.882124"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2007.904681"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2005.01.005"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/4233.992164"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2006.873684"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2005.12.001"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2002.804425"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2012.10.005"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1186\/s12968-014-0056-2"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"5:1?5:15","DOI":"10.1147\/JRD.2017.2708299","article-title":"Deep learning ensembles for melanoma\n recognition in dermoscopy images","volume":"61","author":"codella","year":"2017","journal-title":"IBM J Res Develop"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2010.12.004"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2482072016"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2013.05.002"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCIMAGING.111.966754"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2004.10.010"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2009.2014545"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCIMAGING.112.980037"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/S1076-6332(03)00537-3"},{"key":"ref1","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1161\/CIR.0000000000000366","article-title":"Executive summary: Heart disease and stroke\n statistics–2016 update: A report from the American Heart Association","volume":"133","author":"mozaffarian","year":"2016","journal-title":"Circulation"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-85988-8_14"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/42.925294"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2355175"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2012.02.011"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2004.06.013"},{"article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","year":"2015","author":"ioffe","key":"ref42"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.01.005"},{"article-title":"Adam: Method for stochastic optimization","year":"2014","author":"kingma","key":"ref41"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2012.10.004"},{"key":"ref44","first-page":"1493","article-title":"Learning discriminative representations from RGB-D video data","author":"liu","year":"0","journal-title":"Proc Int Joint Conf Artif Intell"},{"key":"ref26","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical\n image segmentation","volume":"9351","author":"ronneberger","year":"0","journal-title":"Proc Int Conf Med Image Comput Comput -Assisted Intervention"},{"key":"ref43","first-page":"1929","article-title":"Dropout: A simple way to prevent neural\n networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"}],"container-title":["IEEE Transactions on Biomedical Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10\/8440576\/08067513.pdf?arnumber=8067513","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T12:18:06Z","timestamp":1643199486000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8067513\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9]]},"references-count":46,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tbme.2017.2762762","relation":{},"ISSN":["0018-9294","1558-2531"],"issn-type":[{"type":"print","value":"0018-9294"},{"type":"electronic","value":"1558-2531"}],"subject":[],"published":{"date-parts":[[2018,9]]}}}