ML Anthology

A Multi-Resolution Framework for Diffusion Tensor Images

Luc Florack, Laura Astola
CVPRW 2008 pp. 1-7
doi:10.1109/CVPRW.2008.4562966 /cvprw/2008/florack2008cvprw-multiresolution/

Abstract

A new scale space paradigm is proposed for multi-resolution analysis of diffusion tensor images (DTI). An a priori consistency requirement is stipulated, which precludes a linear model. A nonlinear adaptation is proposed to remedy the problem. Subsequently it is shown how differentiation can be operationalized. Considerations in this paper are relevant for DTI analysis in a differential geometric framework, in which the DTI image imposes a Riemannian structure. It adds further support in favor of the ldquogeometric rationalerdquo, and opens the door for a multi-resolution approach towards fibre tracking, connectivity analysis, and so forth.

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Cite

Text

Florack and Astola. "A Multi-Resolution Framework for Diffusion Tensor Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008. doi:10.1109/CVPRW.2008.4562966

Markdown

[Florack and Astola. "A Multi-Resolution Framework for Diffusion Tensor Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008.](https://mlanthology.org/cvprw/2008/florack2008cvprw-multiresolution/) doi:10.1109/CVPRW.2008.4562966

BibTeX

@inproceedings{florack2008cvprw-multiresolution,
  title     = {{A Multi-Resolution Framework for Diffusion Tensor Images}},
  author    = {Florack, Luc and Astola, Laura},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2008},
  pages     = {1-7},
  doi       = {10.1109/CVPRW.2008.4562966},
  url       = {https://mlanthology.org/cvprw/2008/florack2008cvprw-multiresolution/}
}