Quantification of tumor heterogeneity using PET/MRI and machine learning

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dc.contributor.advisor Pichler, Bernd J. (Prof. Dr.)
dc.contributor.author Katiyar, Prateek
dc.date.accessioned 2019-08-27T08:11:21Z
dc.date.available 2019-08-27T08:11:21Z
dc.date.issued 2021-07-25
dc.identifier.uri http://hdl.handle.net/10900/91946
dc.identifier.uri http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-919462 de_DE
dc.identifier.uri http://dx.doi.org/10.15496/publikation-33327
dc.description.abstract Despite a broad understanding that solid tumors exhibit significant tissue heterogeneity, clinical trials have not seen a remarkable development in techniques that aid in characterizing cancer. Needle biopsies often represent only a partial view of the tumor profile, lacking the ability to comprehensively reflect spatiotemporal phenotypic changes. Recent multimodal multiparametric imaging techniques could provide further valuable insights if the complementary imaging information is sufficiently analyzed. Therefore, in this work I developed and applied machine learning methods on multiparametric positron emission tomography (PET) and magnetic resonance imaging (MRI) datasets, acquired using mice bearing subcutaneous tumors, to obtain a precise spatio-temporal characterization of intratumor heterogeneity. en
dc.description.abstract Dissertation ist gesperrt bis 25. Juli 2021 ! de_DE
dc.language.iso en de_DE
dc.publisher Universität Tübingen de_DE
dc.rights ubt-podok de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_mit_pod.php?la=de de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_mit_pod.php?la=en en
dc.subject.classification Maschinelles Lernen de_DE
dc.subject.ddc 610 de_DE
dc.subject.other Tumor heterogeneity en
dc.subject.other PET/MRI en
dc.subject.other Multiparametric imaging en
dc.subject.other Oncology en
dc.title Quantification of tumor heterogeneity using PET/MRI and machine learning en
dc.type Dissertation de_DE
dcterms.dateAccepted 2019-06-07
utue.publikation.fachbereich Medizin de_DE
utue.publikation.fakultaet 4 Medizinische Fakultät de_DE
utue.publikation.noppn yes de_DE


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