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.
|Title of host publication||2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops 2008, Anchorage AK, USA, June 23-28, 2008)|
|Place of Publication||Piscataway NJ|
|Publisher||Institute of Electrical and Electronics Engineers|
|Publication status||Published - 2008|
Florack, L. M. J., & Astola, L. J. (2008). A multi-resolution framework for diffusion tensor images. In 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops 2008, Anchorage AK, USA, June 23-28, 2008) (pp. 1-7). Piscataway NJ: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CVPRW.2008.4562966