{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T16:03:24Z","timestamp":1775837004689,"version":"3.50.1"},"reference-count":46,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,7]]},"DOI":"10.1109\/ijcnn48605.2020.9207220","type":"proceedings-article","created":{"date-parts":[[2020,9,29]],"date-time":"2020-09-29T20:40:33Z","timestamp":1601412033000},"page":"1-8","source":"Crossref","is-referenced-by-count":18,"title":["Brain MRI Tumor Segmentation with Adversarial Networks"],"prefix":"10.1109","author":[{"given":"Edoardo","family":"Giacomello","sequence":"first","affiliation":[]},{"given":"Daniele","family":"Loiacono","sequence":"additional","affiliation":[]},{"given":"Luca","family":"Mainardi","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","article-title":"Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BraTS challenge","volume":"abs 1811 2629","author":"bakas","year":"2018","journal-title":"CoRR"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2377694"},{"key":"ref33","first-page":"3","article-title":"Rectifier nonlinearities improve neural network acoustic models","volume":"30","author":"maas","year":"2013","journal-title":"Proc ICML"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref31","first-page":"396","article-title":"Handwritten digit recognition with a back-propagation network","author":"lecun","year":"1990","journal-title":"Advances in neural information processing systems"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.79"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00917"},{"key":"ref36","author":"mitchell","year":"1997","journal-title":"Machine Learning"},{"key":"ref35","first-page":"807","article-title":"Rectified linear units improve restricted boltzmann machines","author":"nair","year":"2010","journal-title":"Proceedings of the 27th International Conference on Machine Learning (ICML-10)"},{"key":"ref34","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","volume":"abs 1502 3167","author":"ioffe","year":"2015","journal-title":"CoRR"},{"key":"ref10","article-title":"How transferable are features in deep neural networks?","volume":"abs 1411 1792","author":"yosinski","year":"2014","journal-title":"CoRR"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8655(00)00112-4"},{"key":"ref11","article-title":"Deep learning for multi-task medical image segmentation in multiple modalities","volume":"abs 1704 3379","author":"moeskops","year":"2017","journal-title":"CoRR"},{"key":"ref12","article-title":"A transfer-learning approach for accelerated MRI using deep neural networks","volume":"abs 1710 2615","author":"dar","year":"2017","journal-title":"CoRR"},{"key":"ref13","article-title":"A transfer learning approach for automated segmentation of prostate whole gland and transition zone in diffusion weighted mri","author":"motamed","year":"2019"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"777","DOI":"10.1007\/978-3-030-00934-2_86","article-title":"Tumor-aware, adversarial domain adaptation from ct to mri for lung cancer segmentation","author":"jiang","year":"2018","journal-title":"Medical Image Computing and Computer Assisted Intervention &#x2013; MICCAI 2018"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66179-7_59"},{"key":"ref16","article-title":"Transferring gans: Generating images from limited data","author":"wang","year":"2018","journal-title":"ECCV"},{"key":"ref17","first-page":"5767","article-title":"Improved training of wasserstein gans","author":"gulrajani","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref18","article-title":"Mind2mind : transfer learning for gans","volume":"abs 1906 11613","author":"fr\u00e9gier","year":"2019","journal-title":"CoRR"},{"key":"ref19","article-title":"Wasserstein GAN","author":"arjovsky","year":"2017"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32245-8_9"},{"key":"ref4","article-title":"Semantic segmentation using adversarial networks","volume":"abs 1611 8408","author":"luc","year":"2016","journal-title":"CoRR"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00889-5_23"},{"key":"ref3","article-title":"Segan: Adversarial network with multi-scale $l_1$ loss for medical image segmentation","volume":"abs 1706 1805","author":"xue","year":"2017","journal-title":"CoRR"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2009.5459211"},{"key":"ref29","article-title":"Auto-Encoding Variational Bayes","author":"kingma","year":"2013"},{"key":"ref5","article-title":"The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results","author":"everingham","year":"0"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.05.004"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-67558-9_7"},{"key":"ref2","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.media.2016.10.004","article-title":"Efficient multi-scale 3d cnn with fully connected crf for accurate brain lesion segmentation","volume":"36","author":"kamnitsas","year":"2017","journal-title":"Medical Image Analysis"},{"key":"ref1","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":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/s00365-006-0663-2"},{"key":"ref20","article-title":"Image synthesis in multi-contrast MRI with conditional generative adversarial networks","volume":"abs 1802 1221","author":"dar","year":"2018","journal-title":"CoRR"},{"key":"ref45","first-page":"26","article-title":"Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude","volume":"4","author":"tieleman","year":"2012","journal-title":"COURSERA Neural Networks for Machine Learning"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2945521"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref42","article-title":"TensorFlow: Large-scale machine learning on heterogeneous systems","author":"abadi","year":"2015"},{"key":"ref24","article-title":"Simultaneous synthesis of FLAIR and segmentation of white matter hypointensities from T1 mris","volume":"abs 1808 6519","author":"orbes-arteaga","year":"2018","journal-title":"CoRR"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/S0034-4257(97)00083-7"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2018.8363653"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/2723872.2723882"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46723-8_54"},{"key":"ref43","first-page":"2","article-title":"Docker: lightweight linux containers for consistent development and deployment","volume":"2014","author":"merkel","year":"2014","journal-title":"Linux Journal"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2019.8803808"}],"event":{"name":"2020 International Joint Conference on Neural Networks (IJCNN)","location":"Glasgow, United Kingdom","start":{"date-parts":[[2020,7,19]]},"end":{"date-parts":[[2020,7,24]]}},"container-title":["2020 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9200848\/9206590\/09207220.pdf?arnumber=9207220","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T17:54:08Z","timestamp":1656438848000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9207220\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7]]},"references-count":46,"URL":"https:\/\/doi.org\/10.1109\/ijcnn48605.2020.9207220","relation":{},"subject":[],"published":{"date-parts":[[2020,7]]}}}