{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T10:22:11Z","timestamp":1760955731746,"version":"3.37.3"},"reference-count":33,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/OAPA.html"}],"funder":[{"DOI":"10.13039\/100006190","name":"National Key Research and Development Program","doi-asserted-by":"publisher","award":["2016YFC0106500\/2","SQ2017ZY040217\/03","NSFC-Guangdong Union10.13039\/501100001809","U1401254"],"award-info":[{"award-number":["2016YFC0106500\/2","SQ2017ZY040217\/03","NSFC-Guangdong Union10.13039\/501100001809","U1401254"]}],"id":[{"id":"10.13039\/100006190","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"NSFC-Shenzhen Union","doi-asserted-by":"publisher","award":["U1613221"],"award-info":[{"award-number":["U1613221"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangdong Scientific and Technology Program","award":["2015B020214005"],"award-info":[{"award-number":["2015B020214005"]}]},{"name":"Shenzhen Key Basic Science Program","award":["JCYJ20170413162213765"],"award-info":[{"award-number":["JCYJ20170413162213765"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2018]]},"DOI":"10.1109\/access.2017.2781278","type":"journal-article","created":{"date-parts":[[2017,12,8]],"date-time":"2017-12-08T20:37:49Z","timestamp":1512765469000},"page":"2005-2015","source":"Crossref","is-referenced-by-count":24,"title":["Automatic Magnetic Resonance Image Prostate Segmentation Based on Adaptive Feature Learning Probability Boosting Tree Initialization and CNN-ASM Refinement"],"prefix":"10.1109","volume":"6","author":[{"given":"Baochun","family":"He","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Deqiang","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingmao","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0075-979X","authenticated-orcid":false,"given":"Fucang","family":"Jia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"year":"2015","journal-title":"Github Repository","key":"ref33"},{"doi-asserted-by":"publisher","key":"ref32","DOI":"10.1186\/s13040-016-0117-1"},{"key":"ref31","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"},{"doi-asserted-by":"publisher","key":"ref30","DOI":"10.1109\/CVPR.2015.7298965"},{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.1109\/TBME.2013.2289306"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1109\/TMI.2015.2496296"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1016\/j.media.2010.09.002"},{"key":"ref13","first-page":"1","article-title":"Automatic prostate segmentation in MR images with a probabilistic active shape model","author":"kirschner","year":"2012","journal-title":"Proc Med Image Comput Comput -Assisted Intervent Conf Prostate Segment Challenge"},{"key":"ref14","first-page":"1","article-title":"A random forest based classification approach to prostate segmentation in MRI","author":"ghose","year":"2012","journal-title":"Proc Med Image Comput Comput -Assist Intervent Conf Prostate Segment Challenge"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1109\/TMI.2015.2508280"},{"key":"ref16","first-page":"1","article-title":"A multi-atlas approach for prostate segmentation in MR images","author":"litjens","year":"2012","journal-title":"Proc Med Image Comput Comput -Assist Intervent Conf Prostate Segment Challenge"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1016\/j.media.2013.12.002"},{"key":"ref18","first-page":"1","article-title":"Fully automatic segmentation of the prostate using active appearance models","author":"vincent","year":"2012","journal-title":"Proc Med Image Comput Comput -Assist Intervent Conf Prostate Segment Challenge"},{"key":"ref19","first-page":"1","article-title":"Prostate MR image segmentation using 3D active appearance models","author":"maan","year":"2012","journal-title":"Proc Med Image Comput Comput -Assist Intervent Conf Prostate Segment Challenge"},{"key":"ref28","first-page":"94131g-1","article-title":"Deep convolutional networks for pancreas segmentation in CT imaging","volume":"9413","author":"roth","year":"2015","journal-title":"Proc SPIE"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1118\/1.2842076"},{"key":"ref27","first-page":"139","article-title":"Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks","volume":"9041","author":"cruzroa","year":"2014","journal-title":"Proc SPIE"},{"doi-asserted-by":"publisher","key":"ref3","DOI":"10.1118\/1.4946817"},{"key":"ref6","first-page":"1","article-title":"Multi-atlas segmentation of the prostate: A zooming process with robust registration and atlas selection","author":"ou","year":"2012","journal-title":"Proc Med Image Comput Comput -Assist Intervention Conf Prostate Segment Challenge"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.1118\/1.4944498"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1109\/TMI.2012.2211377"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.1088\/0031-9155\/61\/22\/8070"},{"key":"ref7","first-page":"12","article-title":"An automatic multi-atlas based prostate segmentation using local appearance-specific atlases and patch-based voxel weighting","author":"gao","year":"2012","journal-title":"Proc Med Image Comput Comput -Assist Intervent Conf Prostate Segment Challenge"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1006\/cviu.1995.1004"},{"doi-asserted-by":"publisher","key":"ref9","DOI":"10.1118\/1.4914379"},{"year":"2014","journal-title":"Prostate Cancer 2014","key":"ref1"},{"key":"ref20","first-page":"1","article-title":"Deformable landmark-free active appearance models: Application to segmentation of multi-institutional prostate MRI data","author":"toth","year":"2012","journal-title":"Proc Med Image Comput Comput -Assist Intervent Conf Prostate Segment Challenge"},{"doi-asserted-by":"publisher","key":"ref22","DOI":"10.1117\/1.JMI.3.1.014003"},{"key":"ref21","first-page":"1","article-title":"Region-specific hierarchical segmentation of MR prostate using discriminative learning","author":"birkbeck","year":"2012","journal-title":"Proc Med Image Comput Comput -Assist Intervent Conf Prostate Segment Challenge"},{"key":"ref24","first-page":"1589","article-title":"Probabilistic boosting-tree: Learning discriminative models for classification, recognition, and clustering","author":"tu","year":"2005","journal-title":"Proc Int Conf Comput Vis"},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.1016\/j.media.2008.02.001"},{"doi-asserted-by":"publisher","key":"ref26","DOI":"10.1038\/nature14539"},{"doi-asserted-by":"publisher","key":"ref25","DOI":"10.1007\/978-1-4939-0600-0"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8274985\/08170205.pdf?arnumber=8170205","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T03:00:23Z","timestamp":1633921223000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/8170205\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/access.2017.2781278","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2018]]}}}