{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T21:42:36Z","timestamp":1768772556567,"version":"3.49.0"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Basic Research Program of China","doi-asserted-by":"publisher","award":["2018YFC0116400"],"award-info":[{"award-number":["2018YFC0116400"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003399","name":"Science and Technology Commission of Shanghai Municipality","doi-asserted-by":"publisher","award":["19QC1400600"],"award-info":[{"award-number":["19QC1400600"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003399","name":"Science and Technology Commission of Shanghai Municipality","doi-asserted-by":"publisher","award":["17411953300"],"award-info":[{"award-number":["17411953300"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003399","name":"Science and Technology Commission of Shanghai Municipality","doi-asserted-by":"publisher","award":["18JC1420305"],"award-info":[{"award-number":["18JC1420305"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Pujiang Program","award":["19PJ1406800"],"award-info":[{"award-number":["19PJ1406800"]}]},{"DOI":"10.13039\/501100004921","name":"Interdisciplinary Program of Shanghai Jiao Tong University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004921","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/tip.2020.3003735","type":"journal-article","created":{"date-parts":[[2020,6,25]],"date-time":"2020-06-25T20:19:15Z","timestamp":1593116355000},"page":"7497-7510","source":"Crossref","is-referenced-by-count":25,"title":["Task Decomposition and Synchronization for Semantic Biomedical Image Segmentation"],"prefix":"10.1109","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3903-1333","authenticated-orcid":false,"given":"Xuhua","family":"Ren","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7243-9977","authenticated-orcid":false,"given":"Sahar","family":"Ahmad","sequence":"additional","affiliation":[]},{"given":"Lichi","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0763-2313","authenticated-orcid":false,"given":"Lei","family":"Xiang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0385-8988","authenticated-orcid":false,"given":"Dong","family":"Nie","sequence":"additional","affiliation":[]},{"given":"Fan","family":"Yang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3490-3836","authenticated-orcid":false,"given":"Qian","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7934-5698","authenticated-orcid":false,"given":"Dinggang","family":"Shen","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.549"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/VCIP.2017.8305148"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/s11682-015-9480-7"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.343"},{"key":"ref31","article-title":"Task decomposition and synchronization for semantic biomedical image segmentation","author":"ren","year":"2019","journal-title":"arXiv 1905 08720"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.49"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.32"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.11.004"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.79"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46976-8_18"},{"key":"ref29","first-page":"801","article-title":"Encoder-decoder with atrous separable convolution for semantic image segmentation","author":"chen","year":"2018","journal-title":"Proc Eur Conf Comput Vis (ECCV)"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2005.09.054"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00034"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-bioeng-071516-044442"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsych.2007.03.015"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00968"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.04.041"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.398"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00866"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2377694"},{"key":"ref51","first-page":"234","article-title":"No new-net","author":"isensee","year":"2018","journal-title":"International MICCAI Brainlesion Workshop"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1117\/12.2512518"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-55524-9_14"},{"key":"ref54","first-page":"497","article-title":"Learning contextual and attentive information for brain tumor segmentation","author":"zhou","year":"2018","journal-title":"International MICCAI Brainlesion Workshop"},{"key":"ref53","first-page":"311","article-title":"3D MRI brain tumor segmentation using autoencoder regularization","author":"myronenko","year":"2018","journal-title":"International MICCAI Brainlesion Workshop"},{"key":"ref52","first-page":"456","article-title":"Ensembles of densely-connected cnns with label-uncertainty for brain tumor segmentation","author":"mckinley","year":"2018","journal-title":"International MICCAI Brainlesion Workshop"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref11","article-title":"Multi-scale context aggregation by dilated convolutions","author":"yu","year":"2015","journal-title":"arXiv 1511 07122"},{"key":"ref40","first-page":"4898","article-title":"Understanding the effective receptive field in deep convolutional neural networks","author":"luo","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/DASC\/PiCom\/CBDCom\/CyberSciTech.2019.00144"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.01.103"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1117\/12.2512451"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_40"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref17","article-title":"An overview of multi-task learning in deep neural networks","author":"ruder","year":"2017","journal-title":"ArXiv 1706 05098"},{"key":"ref18","article-title":"GradNorm: Gradient normalization for adaptive loss balancing in deep multitask networks","author":"chen","year":"2017","journal-title":"arXiv 1711 02257"},{"key":"ref19","first-page":"178","article-title":"Automatic brain tumor segmentation using cascaded anisotropic convolutional neural networks","author":"wang","year":"2017","journal-title":"International MICCAI Brainlesion Workshop"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00747"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.660"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_17"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.178"},{"key":"ref7","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Proc Int Conf Med Image Comput Comput -Assist Intervent"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.101570"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"ref46","article-title":"2018 robotic scene segmentation challenge","author":"allan","year":"2020","journal-title":"arXiv 2001 11190"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2018.01.025"},{"key":"ref48","article-title":"Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge","author":"bakas","year":"2018","journal-title":"arXiv 1811 02629"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2020.00027"},{"key":"ref42","article-title":"Network in network","author":"lin","year":"2013","journal-title":"arXiv 1312 4400"},{"key":"ref41","article-title":"Rethinking atrous convolution for semantic image segmentation","author":"chen","year":"2017","journal-title":"arXiv 1706 05587"},{"key":"ref44","first-page":"265","article-title":"Tensorflow: A system for large-scale machine learning","author":"abadi","year":"2016","journal-title":"Proc of USENIX Symp on Operating Systems Design and Implementation (OSDI)"},{"key":"ref43","first-page":"8026","article-title":"Pytorch: An imperative style, high-performance deep learning library","author":"paszke","year":"2019","journal-title":"Proc Adv Neural Inf Process Syst"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/8835130\/09126262.pdf?arnumber=9126262","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T14:39:04Z","timestamp":1651070344000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9126262\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":56,"URL":"https:\/\/doi.org\/10.1109\/tip.2020.3003735","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}