{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T06:34:50Z","timestamp":1763620490268,"version":"3.28.0"},"reference-count":22,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,8]]},"DOI":"10.1109\/icpr.2018.8545754","type":"proceedings-article","created":{"date-parts":[[2018,11,29]],"date-time":"2018-11-29T19:17:38Z","timestamp":1543519058000},"page":"3814-3819","source":"Crossref","is-referenced-by-count":17,"title":["Fully convolutional neural networks for prostate cancer detection using multi-parametric magnetic resonance images: an initial investigation"],"prefix":"10.1109","author":[{"given":"Yunzhi","family":"Wang","sequence":"first","affiliation":[]},{"given":"Bin","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Dashan","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Jiao","family":"Wang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2303821"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref12","first-page":"91","article-title":"Faster R-CNN: Towards realtime object detection with region proposal networks","author":"ren","year":"2015","journal-title":"Advances in neural information processing systems"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"lecun","year":"2015","journal-title":"Nature"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1117\/1.JMI.4.4.041302"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.79"},{"key":"ref17","first-page":"66","article-title":"Volumetric ConvNets with Mixed Residual Connections for Automated Prostate Segmentation from 3D MR Images","author":"yu","year":"2017","journal-title":"AAAI"},{"journal-title":"Adversarial Networks for the Detection of Aggressive Prostate Cancer","year":"2017","author":"kohl","key":"ref18"},{"key":"ref19","first-page":"1013405","article-title":"Convolutional Neural Network Based Deep-learning Architecture for Prostate Cancer Detection on Multiparametric Magnetic Resonance Images","author":"tsehay","year":"2017","journal-title":"SPIE Medical Imaging"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.07.2211"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.20626"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/789561"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1002\/pros.20124"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1118\/1.2842076"},{"key":"ref7","first-page":"10","article-title":"Fast automatic multi-atlas segmentation of the prostate from 3D MR images","author":"dowling","year":"2011","journal-title":"International Workshop on Prostate Cancer Imaging"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.22075"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21332"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2012.2201498"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1002\/mp.12116"},{"key":"ref22","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"ar Xiv preprint ar Xiv 1412 6980"},{"journal-title":"Tensorflow Large-scale machine learning on heterogeneous distributed systems","year":"2016","author":"abadi","key":"ref21"}],"event":{"name":"2018 24th International Conference on Pattern Recognition (ICPR)","start":{"date-parts":[[2018,8,20]]},"location":"Beijing","end":{"date-parts":[[2018,8,24]]}},"container-title":["2018 24th International Conference on Pattern Recognition (ICPR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8527858\/8545020\/08545754.pdf?arnumber=8545754","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T09:22:37Z","timestamp":1643275357000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8545754\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/icpr.2018.8545754","relation":{},"subject":[],"published":{"date-parts":[[2018,8]]}}}