Uncertainty and Reproducibility in Medical Visualization

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dc.contributor.authorLinsen, Larsen_US
dc.contributor.authorAl-Taie, Ahmeden_US
dc.contributor.authorRistovski, Gordanen_US
dc.contributor.authorPreusser, Tobiasen_US
dc.contributor.authorHahn, Horst K.en_US
dc.contributor.editorKai Lawonn and Mario Hlawitschka and Paul Rosenthalen_US
dc.date.accessioned2016-06-09T09:31:51Z
dc.date.available2016-06-09T09:31:51Z
dc.date.issued2016en_US
dc.description.abstractThe medical visualization pipeline is affected by various sources of uncertainty. Many errors may occur and several assumptions are made in the various processing steps from the image acquisition to the rendering of the visualization output, which induce uncertainty. High uncertainty leads to low robustness of the algorithms impacting reproducibility of the results. We present how uncertainty can be mathematically described in the medical context. Moreover, in medical applications, the visualization is typically based on a segmentation of the medical images. We propose a method to capture uncertainty in image segmentation and present extensions to ensemble and multi-modal image segmentation.en_US
dc.description.sectionheadersReproducibility in Medical Visualizationen_US
dc.description.seriesinformationEuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3)en_US
dc.identifier.doi10.2312/eurorv3.20161107en_US
dc.identifier.isbn978-3-03868-017-8en_US
dc.identifier.issn-en_US
dc.identifier.issn1017-4656en_US
dc.identifier.pages1-3en_US
dc.identifier.urihttps://doi.org/10.2312/eurorv3.20161107en_US
dc.identifier.urihttps://diglib.eg.org:443/handle/10
dc.publisherThe Eurographics Associationen_US
dc.subjecten_US
dc.titleUncertainty and Reproducibility in Medical Visualizationen_US
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