Scalar anisotropy indices are important means for the analysis and visualization of diffusion tensor fields. While the propagation of uncertainty and errors has been studied for a variety measures, this chapter additionally considers the extraction of isosurfaces from anisotropy fields. We use the numerical condition to estimate the uncertainty propagation from the DT's eigenvalues via fractional (FA) and relative anisotropy (RA) to the position and shape of isosurfaces. Using level crossing

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... babilities we quantify and visualize the spatial distribution of uncertain isosurfaces. The superiority of FA to RA in terms of uncertainty propagation that was shown for anisotropy images in the literature does not hold for isosurfaces extracted from these images. Instead, our results indicate that for the purpose of isosurface extraction both measures perform approximately equally well.