{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T22:49:50Z","timestamp":1791326990929,"version":"4.3.1"},"reference-count":85,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","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\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["DP160103675"],"award-info":[{"award-number":["DP160103675"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2020,1]]},"DOI":"10.1109\/tmi.2019.2923601","type":"journal-article","created":{"date-parts":[[2019,6,17]],"date-time":"2019-06-17T15:34:41Z","timestamp":1560785681000},"page":"204-217","source":"Crossref","is-referenced-by-count":235,"title":["Co-Learning Feature Fusion Maps From PET-CT Images of Lung Cancer"],"prefix":"10.1109","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6236-7324","authenticated-orcid":false,"given":"Ashnil","family":"Kumar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Fulham","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3381-214X","authenticated-orcid":false,"given":"Dagan","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5960-1060","authenticated-orcid":false,"given":"Jinman","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2572683"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2041468"},{"key":"ref71","article-title":"A guide to convolution arithmetic for deep learning","author":"dumoulin","year":"2016","journal-title":"ArXiv 1603 07285"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2015.04.018"},{"key":"ref76","first-page":"265","article-title":"TensorFlow: A system for large-scale machine learning","author":"abadi","year":"2016","journal-title":"Proc 11th USENIX Conf Oper Syst Design Implement"},{"key":"ref77","article-title":"cuDNN: Efficient primitives for deep learning","author":"chetlur","year":"2014","journal-title":"Arxiv 1410 0759"},{"key":"ref74","first-page":"1139","article-title":"On the importance of initialization and momentum in deep learning","author":"sutskever","year":"2013","journal-title":"Proc ICML"},{"key":"ref39","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":"ref75","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","author":"han","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.10.004"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46723-8_48"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2009.2025006"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2016.05.004"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.10.009"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.02.005"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-009-1297-4"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s12149-013-0719-3"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.111.092767"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2236346"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.amjoto.2017.10.009"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.5244\/C.28.6"},{"key":"ref61","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-018-30111-7","article-title":"Maximum standardized uptake value (SUV $_{max}$ ) of primary tumor predicts occult neck metastasis in oral cancer","volume":"8","author":"morand","year":"2018","journal-title":"Sci Rep"},{"key":"ref63","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2488902"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1016\/S0378-3758(00)00115-4"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1186\/s12885-015-1867-8"},{"key":"ref65","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","volume":"37","author":"ioffe","year":"2015","journal-title":"Proc ICML"},{"key":"ref66","first-page":"3","article-title":"Rectifier nonlinearities improve neural network acoustic models","volume":"30","author":"maas","year":"2013","journal-title":"ICML Workshop on Deep Learning for Audio Speech and Language Processing"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2014.6943982"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.59"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1111\/1467-8659.00356"},{"key":"ref69","first-page":"1081","article-title":"&#x2018;Flying through&#x2019; and &#x2018;flying around&#x2019; a PET\/CT scan: Pilot study and development of 3D integrated 18F-FDG PET\/CT for virtual bronchoscopy and colonoscopy","volume":"47","author":"quon","year":"2006","journal-title":"J Nucl Med"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2422051113"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.09.3193"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2012.2185057"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2013.11.003"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10404-1_71"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-012-2309-3"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-014-2961-x"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1148\/rg.254035156"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-005-0088-y"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2017170700"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/aaf44b"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2006.09.039"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2003.10.044"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/42.929615"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2008.239"},{"key":"ref55","first-page":"4","article-title":"Understanding the standardized uptake value, its methods, and implications for usage","volume":"45","author":"thie","year":"2004","journal-title":"J Nucl Med"},{"key":"ref54","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1002\/mp.13331","article-title":"Simultaneous cosegmentation of tumors in PET-CT images using deep fully convolutional networks","volume":"46","author":"zhong","year":"2019","journal-title":"Med Phys"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.10.099"},{"key":"ref52","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Proc MICCAI"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2016.11.008"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/2391925"},{"key":"ref40","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.79"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2018.8363561"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0123694"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2013.2283658"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2013.2285931"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.549"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2013.2263388"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-22092-0_21"},{"key":"ref83","first-page":"12","article-title":"Inception-v4, inception-resnet and the impact of residual connections on learning","volume":"4","author":"szegedy","year":"2017","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref19","first-page":"327","article-title":"Deep learning for classification of benign and malignant bone lesions in [F-18]NaF PET\/CT images","volume":"59","author":"bradshaw","year":"2018","journal-title":"J Nucl Med"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1002\/mp.13141"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2013.05.004"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.108.057307"},{"key":"ref6","author":"amin","year":"2010","journal-title":"AJCC Cancer Staging Manual"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1378\/chest.08-0978"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2016.03.003"},{"key":"ref8","first-page":"11146","article-title":"The role of FDG PET\/CT in evaluation of mediastinal masses and neurogenic tumors of chest wall","volume":"8","author":"tatci","year":"2015","journal-title":"Clinical and Experimental Medical Journal"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1245\/s10434-010-0985-4"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-61188-4_12"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1118\/1.4948498"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2535865"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2015.2425041"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.398"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.12.061"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2528162"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2016.2635663"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2535302"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/8946770\/08737963.pdf?arnumber=8737963","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T09:59:16Z","timestamp":1651053556000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8737963\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1]]},"references-count":85,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2019.2923601","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,1]]}}}