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dc.contributor.authorRaidou, Renata G.en_US
dc.contributor.editorKai Lawonn and Noeska Smit and Lars Linsen and Robert Kosaraen_US
dc.date.accessioned2018-06-02T17:58:01Z
dc.date.available2018-06-02T17:58:01Z
dc.date.issued2018
dc.identifier.isbn978-3-03868-066-6
dc.identifier.urihttp://dx.doi.org/10.2312/eurorv3.20181143
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurorv320181143
dc.description.abstractRadiotherapy is one of the most common treatment strategy for prostate cancer. Prior to radiotherapy, a complex process consisting of several steps is employed to create an optimal treatment plan. However, all these steps include several sources of uncertainty, which can be detrimental for the successful outcome of the treatment. In this work, we present a number of strategies from the field of Visual Analytics that have been recently designed and implemented, for the visualization of data, processes and uncertainties at each step of the planning pipeline. We additionally document our opinion on topics that have not been yet addressed, and could be interesting directions for future work.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.8 [Computer Graphics]
dc.subjectApplications
dc.subjectApplications
dc.subjectJ.3 [Computer Applications]
dc.subjectLife and Medical Sciences
dc.subjectLife and Medical Sciences
dc.titleUncertainty Visualization: Recent Developments and Future Challenges in Prostate Cancer Radiotherapy Planningen_US
dc.description.seriesinformationEuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3)
dc.description.sectionheadersSession 1
dc.identifier.doi10.2312/eurorv3.20181143
dc.identifier.pages13-17


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