{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T18:10:37Z","timestamp":1772907037702,"version":"3.50.1"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T00:00:00Z","timestamp":1556668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T00:00:00Z","timestamp":1556668800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T00:00:00Z","timestamp":1556668800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100012913","name":"Tata Consultancy Services","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100012913","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Biomed. Health Inform."],"published-print":{"date-parts":[[2019,5]]},"DOI":"10.1109\/jbhi.2018.2852635","type":"journal-article","created":{"date-parts":[[2018,7,3]],"date-time":"2018-07-03T18:43:43Z","timestamp":1530643423000},"page":"1151-1162","source":"Crossref","is-referenced-by-count":62,"title":["RACE-Net: A Recurrent Neural Network for Biomedical Image Segmentation"],"prefix":"10.1109","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3646-0650","authenticated-orcid":false,"given":"Arunava","family":"Chakravarty","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jayanthi","family":"Sivaswamy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2187670"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-14-297"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1134\/S1054661817030269"},{"key":"ref32","first-page":"136","article-title":"Boosting convolutional filters with entropy sampling for optic cup and disc image segmentation from fundus images","author":"zilly","year":"0","journal-title":"Proc Int Workshop Mach Learn Med Imag"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2013.2247770"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2012.2187293"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0142830"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.08.103"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-10-368"},{"key":"ref34","first-page":"75","article-title":"Optic disc and cup segmentation from color fundus photograph using graph cut with priors","author":"zheng","year":"0","journal-title":"Proc Med Image Comput Comput -Assisted Intervention"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.10.004"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/IPTA.2014.7001976"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1118\/1.4944498"},{"key":"ref12","first-page":"424","article-title":"3-D U-net: Learning dense volumetric segmentation from sparse annotation","author":"\u00e7i\u00e7ek","year":"0","journal-title":"Proc Int Conf Med Image Comput Comput -Assisted Intervention"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.179"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ACPR.2017.121"},{"key":"ref15","first-page":"3036","article-title":"Combining fully convolutional and recurrent neural networks for 3-D biomedical image segmentation","author":"chen","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref16","first-page":"185","article-title":"Spatial clockwork recurrent neural network for muscle perimysium segmentation","author":"xie","year":"0","journal-title":"Proc Int Conf Med Image Comput Comput -Assisted Intervention"},{"key":"ref17","first-page":"2998","article-title":"Parallel multi-dimensional LSTM, with application to fast biomedical volumetric image segmentation","author":"stollenga","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2765695"},{"key":"ref19","first-page":"17","volume":"5","author":"mitiche","year":"2010","journal-title":"Variational and Level Set Methods in Image Segmentation"},{"key":"ref28","first-page":"1004","article-title":"A comprehensive retinal image dataset for the assessment of glaucoma from the optic nerve head analysis","volume":"2","author":"sivaswamy","year":"2015","journal-title":"JSM Biomedical Imaging Data Papers"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/83.661186"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2017.06.004"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/34.244675"},{"key":"ref6","first-page":"2843","article-title":"Deep neural networks segment neuronal membranes in electron microscopy images","author":"ciresan","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2011.2106509"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/83.902291"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.79"},{"key":"ref7","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"0","journal-title":"Proc Int Conf Med Image Comput Comput -Assisted Intervention"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007979827043"},{"key":"ref9","first-page":"140","article-title":"Deep retinal image understanding","author":"maninis","year":"0","journal-title":"Proc Int Conf Med Image Comput Comput -Assisted Intervention"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/S1361-8415(96)80007-7"},{"key":"ref20","first-page":"74","author":"sapiro","year":"2006","journal-title":"Geometric Partial Differential Equations and Image Analysis"},{"key":"ref22","first-page":"1045","article-title":"Recurrent neural network based language model","author":"mikolov","year":"0","journal-title":"Proc 11th Annu Conf Int Speech Commun Assoc"},{"key":"ref21","article-title":"Theano: A Python framework for fast computation of mathematical expressions","year":"2016"},{"key":"ref42","author":"toboz-gomez","year":"2012","journal-title":"Left atrium segmentation challenge &#x201D;"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"3243","DOI":"10.1109\/TIP.2010.2069690","article-title":"Distance regularized level set evolution and its application to image segmentation","volume":"19","author":"li","year":"2010","journal-title":"IEEE Trans Image Process"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2015.2398818"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/5.58337"},{"key":"ref44","article-title":"Deep active contours","author":"rupprecht","year":"0"},{"key":"ref26","article-title":"Keras","author":"chollet","year":"2015"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref25","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"0","journal-title":"Proc Int Conf Learn Represent"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221020\/8705605\/08402041.pdf?arnumber=8402041","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T20:53:33Z","timestamp":1657745613000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8402041\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5]]},"references-count":44,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2018.2852635","relation":{},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"value":"2168-2194","type":"print"},{"value":"2168-2208","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5]]}}}