GEMSe: Visualization-Guided Exploration of Multi-channel Segmentation Algorithms

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dc.contributor.authorFröhler, Bernharden_US
dc.contributor.authorMöller, Torstenen_US
dc.contributor.authorHeinzl, Christophen_US
dc.contributor.editorKwan-Liu Ma and Giuseppe Santucci and Jarke van Wijken_US
dc.date.accessioned2016-06-09T09:32:42Z
dc.date.available2016-06-09T09:32:42Z
dc.date.issued2016en_US
dc.description.abstractWe present GEMSe, an interactive tool for exploring and analyzing the parameter space of multi-channel segmentation algorithms. Our targeted user group are domain experts who are not necessarily segmentation specialists. GEMSe allows the exploration of the space of possible parameter combinations for a segmentation framework and its ensemble of results. Users start with sampling the parameter space and computing the corresponding segmentations. A hierarchically clustered image tree provides an overview of variations in the resulting space of label images. Details are provided through exemplary images from the selected cluster and histograms visualizing the parameters and the derived output in the selected cluster. The correlation between parameters and derived output as well as the effect of parameter changes can be explored through interactive filtering and scatter plots. We evaluate the usefulness of GEMSe through expert reviews and case studies based on three different kinds of datasets: A synthetic dataset emulating the combination of 3D X-ray computed tomography with data from K-Edge spectroscopy, a three-channel scan of a rock crystal acquired by a Talbot-Lau grating interferometer X-ray computed tomography device, as well as a hyperspectral image.en_US
dc.description.number3en_US
dc.description.sectionheadersVolume Data Applicationsen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume35en_US
dc.identifier.doi10.1111/cgf.12895en_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages191-200en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12895en_US
dc.identifier.urihttps://diglib.eg.org:443/handle/10
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.3.8 [Computer Graphics]en_US
dc.subjectApplicationsen_US
dc.subjecten_US
dc.subjecten_US
dc.subjectI.4.6 [Image Processing and Computer Vision]en_US
dc.subjectSegmentationen_US
dc.subjectPixel classificationen_US
dc.titleGEMSe: Visualization-Guided Exploration of Multi-channel Segmentation Algorithmsen_US
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35-Issue 3
EuroVis16: Eurographics Conference on Visualization