Predicting prostate tumour location from multiparametric MRI using Gaussian kernel support vector machines: a preliminary study

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dc.contributor.author Sun Yu en
dc.contributor.author Reynolds Hayley en
dc.contributor.author Wraith Darren en
dc.contributor.author Williams Scott en
dc.contributor.author Finnegan Mary E en
dc.contributor.author Mitchell Catherine en
dc.contributor.author Murphy Declan en
dc.contributor.author Ebert Martin A en
dc.contributor.author Haworth Annette en
dc.date.accessioned 2020-10-16T04:04:11Z
dc.date.available 2020-10-16T04:04:11Z
dc.date.issued 2017 en
dc.identifier.uri http://hdl.handle.net/2292/53356
dc.publisher Springer en
dc.relation.ispartofseries Australasian physical & engineering sciences in medicine en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.title Predicting prostate tumour location from multiparametric MRI using Gaussian kernel support vector machines: a preliminary study en
dc.type Journal Article en
pubs.begin-page 39 en
pubs.volume 40 en
dc.date.updated 2020-09-24T21:55:14Z en
dc.rights.holder Copyright: The author en
pubs.end-page 49 en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.subtype article en
pubs.elements-id 789341 en
pubs.number 1 en


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