RadEx: Integrated Visual Exploration of Multiparametric Studies for Radiomic Tumor Profiling

dc.contributor.authorMörth, Ericen_US
dc.contributor.authorWagner-Larsen, Karien_US
dc.contributor.authorHodneland, Erlenden_US
dc.contributor.authorKrakstad, Camillaen_US
dc.contributor.authorHaldorsen, Ingfrid S.en_US
dc.contributor.authorBruckner, Stefanen_US
dc.contributor.authorSmit, Noeska N.en_US
dc.contributor.editorEisemann, Elmar and Jacobson, Alec and Zhang, Fang-Lueen_US
dc.date.accessioned2020-10-29T18:51:24Z
dc.date.available2020-10-29T18:51:24Z
dc.date.issued2020
dc.description.abstractBetter understanding of the complex processes driving tumor growth and metastases is critical for developing targeted treatment strategies in cancer. Radiomics extracts large amounts of features from medical images which enables radiomic tumor profiling in combination with clinical markers. However, analyzing complex imaging data in combination with clinical data is not trivial and supporting tools aiding in these exploratory analyses are presently missing. In this paper, we present an approach that aims to enable the analysis of multiparametric medical imaging data in combination with numerical, ordinal, and categorical clinical parameters to validate established and unravel novel biomarkers. We propose a hybrid approach where dimensionality reduction to a single axis is combined with multiple linked views allowing clinical experts to formulate hypotheses based on all available imaging data and clinical parameters. This may help to reveal novel tumor characteristics in relation to molecular targets for treatment, thus providing better tools for enabling more personalized targeted treatment strategies. To confirm the utility of our approach, we closely collaborate with experts from the field of gynecological cancer imaging and conducted an evaluation with six experts in this field.en_US
dc.description.number7
dc.description.sectionheadersVisualization and Interaction
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume39
dc.identifier.doi10.1111/cgf.14172
dc.identifier.issn1467-8659
dc.identifier.pages611-622
dc.identifier.urihttps://doi.org/10.1111/cgf.14172
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14172
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectApplied computing
dc.subjectHealth informatics
dc.subjectHuman centered computing
dc.subjectVisualization design and evaluation methods
dc.titleRadEx: Integrated Visual Exploration of Multiparametric Studies for Radiomic Tumor Profilingen_US
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