Abstract
This paper considers the feature space of DT-MRI as a differential manifold with an affine-invariant metric. We generalise Di Zenzo's structure tensor to tensor-valued images for edge detection. To improve the quality of the edges, we develop a generalised Perona-Malik method for smoothing tensor images. We demonstrate our algorithm on both synthetic and real DT-MRI data. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Zhang, F., & Hancock, E. R. (2006). Smoothing tensor-valued images using anisotropic geodesic diffusion. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4109 LNCS, pp. 83–91). Springer Verlag. https://doi.org/10.1007/11815921_8
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