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dc.contributor.authorLiu, Sidong
dc.contributor.authorCai, Weidong
dc.contributor.authorLiu, Siqi
dc.contributor.authorZhang, Fan
dc.contributor.authorFulham, Michael
dc.contributor.authorFeng, Dagan
dc.contributor.authorPujol, Sonia
dc.contributor.authorKikinis, Ron
dc.date.accessioned2019-06-11
dc.date.available2019-06-11
dc.date.issued2015-09-04
dc.identifier.citationLiu, S., Cai, W., Liu, S. et al. Brain Inf. (2015) 2: 181. https://doi.org/10.1007/s40708-015-0020-4en_AU
dc.identifier.issn2198-4018
dc.identifier.urihttp://hdl.handle.net/2123/20521
dc.description.abstractThe last two decades have witnessed the explosive growth in the development and use of noninvasive neuroimaging technologies that advance the research on human brain under normal and pathological conditions. Multimodal neuroimaging has become a major driver of current neuroimaging research due to the recognition of the clinical benefits of multimodal data, and the better access to hybrid devices. Multimodal neuroimaging computing is very challenging, and requires sophisticated computing to address the variations in spatiotemporal resolution and merge the biophysical/biochemical information. We review the current workflows and methods for multimodal neuroimaging computing, and also demonstrate how to conduct research using the established neuroimaging computing packages and platforms.en_AU
dc.publisherSpringer Openen_AU
dc.relationARC DP140100211
dc.relationARC DP140100211
dc.rights"© Liu, Cai, Liu, Zhang, Fulham, Feng, Pujol, Kikinis 2015. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made."en_AU
dc.subjectMultimodal Neuroimaging, Medical image computingen_AU
dc.titleMultimodal neuroimaging computing: the workflows, methods, and platformsen_AU
dc.typeArticleen_AU
dc.identifier.doihttps://doi.org/10.1007/s40708-015-0020-4
dc.type.pubtypePublisher's versionen_AU


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