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

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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