Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/97439
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dc.contributor.authorMarcu, L.G.-
dc.contributor.authorBezak, E.-
dc.contributor.authorToma-Dasu, I.-
dc.contributor.authorDasu, A.-
dc.date.issued2015-
dc.identifier.citationComputational and Mathematical Methods in Medicine, 2015; 2015:571371-1-571371-2-
dc.identifier.issn1748-670X-
dc.identifier.issn1748-6718-
dc.identifier.urihttp://hdl.handle.net/2440/97439-
dc.descriptionEditorial, abstract not included.-
dc.description.statementofresponsibilityLoredana G. Marcu, Eva Bezak, Iuliana Toma-Dasu, and Alexandru Dasu-
dc.language.isoen-
dc.publisherHindawi Publishing Corporation-
dc.rightsCopyright © 2015 Loredana G. Marcu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.-
dc.source.urihttp://dx.doi.org/10.1155/2015/571351-
dc.subjectHumans-
dc.subjectNeoplasms-
dc.subjectDiagnostic Imaging-
dc.subjectPositron-Emission Tomography-
dc.subjectMedical Oncology-
dc.subjectCell Hypoxia-
dc.subjectAlgorithms-
dc.subjectComputer Simulation-
dc.titlePredictive models of tumour response to treatment using functional imaging techniques-
dc.typeJournal article-
dc.identifier.doi10.1155/2015/571351-
pubs.publication-statusPublished-
dc.identifier.orcidBezak, E. [0000-0002-1315-1735]-
Appears in Collections:Aurora harvest 3
Physics publications

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