{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T14:42:07Z","timestamp":1775486527695,"version":"3.50.1"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2019,2,1]],"date-time":"2019-02-01T00:00:00Z","timestamp":1548979200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,2,1]],"date-time":"2019-02-01T00:00:00Z","timestamp":1548979200000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,2,1]],"date-time":"2019-02-01T00:00:00Z","timestamp":1548979200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,2,1]],"date-time":"2019-02-01T00:00:00Z","timestamp":1548979200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"US National Science Foundation","award":["14-29404"],"award-info":[{"award-number":["14-29404"]}]},{"name":"US National Science Foundation","award":["15-64212"],"award-info":[{"award-number":["15-64212"]}]},{"name":"US National Science Foundation","award":["16-32976"],"award-info":[{"award-number":["16-32976"]}]},{"name":"NCI, NIH","award":["HHSN261200800001E"],"award-info":[{"award-number":["HHSN261200800001E"]}]},{"DOI":"10.13039\/100000161","name":"NIST","doi-asserted-by":"crossref","award":["#70NANB15H329"],"award-info":[{"award-number":["#70NANB15H329"]}],"id":[{"id":"10.13039\/100000161","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000161","name":"NIST","doi-asserted-by":"crossref","award":["#70NANB16H206"],"award-info":[{"award-number":["#70NANB16H206"]}],"id":[{"id":"10.13039\/100000161","id-type":"DOI","asserted-by":"crossref"}]},{"name":"State of Maryland's MPower initiative"},{"DOI":"10.13039\/100007065","name":"Nvidia","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007065","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Visual. Comput. Graphics"],"published-print":{"date-parts":[[2019,2,1]]},"DOI":"10.1109\/tvcg.2018.2796085","type":"journal-article","created":{"date-parts":[[2018,1,19]],"date-time":"2018-01-19T19:19:11Z","timestamp":1516389551000},"page":"1378-1391","source":"Crossref","is-referenced-by-count":33,"title":["Deep-Learning-Assisted Volume Visualization"],"prefix":"10.1109","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5415-7885","authenticated-orcid":false,"given":"Hsueh-Chien","family":"Cheng","sequence":"first","affiliation":[]},{"given":"Antonio","family":"Cardone","sequence":"additional","affiliation":[]},{"given":"Somay","family":"Jain","sequence":"additional","affiliation":[]},{"given":"Eric","family":"Krokos","sequence":"additional","affiliation":[]},{"given":"Kedar","family":"Narayan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4231-4115","authenticated-orcid":false,"given":"Sriram","family":"Subramaniam","sequence":"additional","affiliation":[]},{"given":"Amitabh","family":"Varshney","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/34.868688"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.21136\/CMJ.1973.101168"},{"key":"ref33","first-page":"65","article-title":"Exploiting enclosing membranes and contextual cues for mitochondria segmentation","author":"lucchi","year":"2014","journal-title":"Proc Int Conf Med Image Comput Comput -Assisted Intervention"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/PROC.1979.11328"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-15090-1_11"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2014.2346411"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8659.2008.01182.x"},{"key":"ref36","article-title":"ADADELTA: An adaptive learning rate method","author":"zeiler","year":"2012"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref34","first-page":"i?115","article-title":"Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures","author":"bergstra","year":"2013","journal-title":"Proc Int Conf Int Conf Mach Learn"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/VISUAL.2003.1250414"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/SVVG.2004.16"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/S0097-8493(02)00053-5"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6639343"},{"key":"ref1","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Annu Conf Advances Neural Inf Process Syst"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref22","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref21","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.12934"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/VISUAL.2003.1250384"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/2945.506226"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/37401.37422"},{"key":"ref50","first-page":"647","article-title":"DeCAF: A deep convolutional activation feature for generic visual recognition","author":"donahue","year":"2014","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2011.173"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2528821"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref54","first-page":"126","article-title":"Isotropic reconstruction of 3D fluorescence microscopy images using convolutional neural networks","author":"weigert","year":"2017","journal-title":"Proc Int Conf Med Image Comput Comput -Assisted Intervention"},{"key":"ref53","doi-asserted-by":"crossref","first-page":"1737","DOI":"10.1109\/TVCG.2011.231","article-title":"Saliency-assisted navigation of very large landscape images","volume":"17","author":"ip","year":"2011","journal-title":"IEEE Trans Vis Comput Graph"},{"key":"ref52","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1126\/science.1127647","article-title":"Reducing the dimensionality of data with neural networks","volume":"313","author":"hinton","year":"2006","journal-title":"Sci"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2010.35"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2002.1021579"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772862"},{"key":"ref12","first-page":"69","article-title":"Multi-dimensional reduction and transfer function design using parallel coordinates","author":"zhao","year":"2010","journal-title":"Proc IEEE Int Conf Volume Graph"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2012.105"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2015.2467294"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2009.185"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"2355","DOI":"10.1109\/TVCG.2012.231","article-title":"Hierarchical exploration of volumes using multilevel segmentation of the intensity-gradient histograms","volume":"18","author":"ip","year":"2012","journal-title":"IEEE Trans Vis Comput Graph"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1057\/ivs.2010.6","article-title":"Dimensionality reduction on multi-dimensional transfer functions for multi-channel volume data sets","volume":"9","author":"kim","year":"2010","journal-title":"Inf Vis"},{"key":"ref18","first-page":"1","article-title":"Going deeper with convolutions","author":"szegedy","year":"2014","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref19","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2015","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref4","first-page":"2843","article-title":"Deep neural networks segment neuronal membranes in electron microscopy images","author":"ciresan","year":"2012","journal-title":"Proc Annu Conf Advances Neural Inf Process Syst"},{"key":"ref3","first-page":"1988","article-title":"Deep learning face representation by joint identification-verification","author":"sun","year":"2014","journal-title":"Proc Annu Conf Advances Neural Inf Process Syst"},{"key":"ref6","article-title":"Striving for simplicity: The all convolutional net","author":"springenberg","year":"2015","journal-title":"Proc Workshop Int Conf Learn Represent"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2538465"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-010-0480-1"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2008.162"},{"key":"ref49","first-page":"249","article-title":"Medical applications of multi-field volume rendering and VR techniques","author":"kniss","year":"2004","journal-title":"Proc Joint Eurographics - IEEE Conf Vis"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2008.169"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1111\/1758-2229.12130"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.jsb.2013.11.008"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2377694"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.259"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1126\/science.aab1576"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654889"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.3623"}],"container-title":["IEEE Transactions on Visualization and Computer Graphics"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielaam\/2945\/8594686\/8265023-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/2945\/8594686\/08265023.pdf?arnumber=8265023","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T21:14:19Z","timestamp":1657746859000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8265023\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,2,1]]},"references-count":56,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tvcg.2018.2796085","relation":{},"ISSN":["1077-2626","1941-0506","2160-9306"],"issn-type":[{"value":"1077-2626","type":"print"},{"value":"1941-0506","type":"electronic"},{"value":"2160-9306","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,2,1]]}}}