Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/100142
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dc.contributor.authorLiang, S.-
dc.contributor.authorPanagiotaki, E.-
dc.contributor.authorBongers, A.-
dc.contributor.authorShi, P.-
dc.contributor.authorSved, P.-
dc.contributor.authorWatson, G.-
dc.contributor.authorBourne, R.-
dc.date.issued2016-
dc.identifier.citationNMR in Biomedicine, 2016; 29(5):660-671-
dc.identifier.issn0952-3480-
dc.identifier.issn1099-1492-
dc.identifier.urihttp://hdl.handle.net/2440/100142-
dc.description.abstractAbstract not available-
dc.description.statementofresponsibilitySisi Liang, Eleftheria Panagiotaki, Andre Bongers, Peng Shi, Paul Sved, Geoffrey Watson and Roger Bourne-
dc.language.isoen-
dc.publisherWiley-
dc.rightsCopyright © 2016 John Wiley & Sons, Ltd.-
dc.source.urihttp://dx.doi.org/10.1002/nbm.3510-
dc.subjectDiffusion; prostate; modeling; compartment models; restricted diffusion; microstructure imaging-
dc.titleInformation-based ranking of 10 compartment models of diffusion-weighted signal attenuation in fixed prostate tissue-
dc.typeJournal article-
dc.identifier.doi10.1002/nbm.3510-
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/1026467-
pubs.publication-statusPublished-
dc.identifier.orcidShi, P. [0000-0001-8218-586X]-
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