Strategies for Direct Volume Rendering of Diffusion Tensor Fields
IEEE Transactions on Visualization and Computer Graphics
Tissue Classification Based on 3D Local Intensity Structures for Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
Muliscale Vessel Enhancement Filtering
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
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A common model of second degree variation is an ellipsoid spanned by the magnitudes of the Hessian eigenvalues. We find this model incomplete and often misleading. Here, we present a more complete representation of the information embedded in second degree derivatives. Using spherical harmonics as a basis set, the rotation invariant part of this information is portrayed as an orthonormal shape-space, which is non-redundant in the sense that any local second order variation can be rotated to match one and only one unique prototype in this space. A host of truly rotation invariant and shape discriminative shape factors is readily defined.