Segmentation of DT-MRI Anisotropy Isosurfaces

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dc.contributor.authorSchultz, Thomasen_US
dc.contributor.authorTheisel, Holgeren_US
dc.contributor.authorSeidel, Hans-Peteren_US
dc.contributor.editorK. Museth and T. Moeller and A. Ynnermanen_US
dc.date.accessioned2014-01-31T07:11:05Z
dc.date.available2014-01-31T07:11:05Z
dc.date.issued2007en_US
dc.description.abstractWhile isosurfaces of anisotropy measures for data from diffusion tensor magnetic resonance imaging (DT-MRI) are known to depict major anatomical structures, the anisotropy metric reduces the rich tensor data to a simple scalar field. In this work, we suggest that the part of the data which has been ignored by the metric can be used to segment anisotropy isosurfaces into anatomically meaningful regions. For the implementation, we propose an edge-based watershed method that adapts and extends a method from curvature-based mesh segmentation [MW99]. Finally, we use the segmentation results to enhance visualization of the data.en_US
dc.description.seriesinformationEurographics/ IEEE-VGTC Symposium on Visualizationen_US
dc.identifier.isbn978-3-905673-45-6en_US
dc.identifier.issn1727-5296en_US
dc.identifier.urihttps://doi.org/10.2312/VisSym/EuroVis07/187-194en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.4.6 [Image Processing and Computer Vision]: Region growing, partitioningen_US
dc.titleSegmentation of DT-MRI Anisotropy Isosurfacesen_US
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