Sticky Vector Fields, and Other Geometric Measures on Diffusion Tensor Images
Abstract
This paper is about geometric measures in diffusion tensor imaging (DTI) analysis, and it is a continuation of our previous work (L. Astola et al., 2007), where we discussed two measures for diffusion tensor (DT) image (fiber tractography) analysis. Its contribution is threefold. First, we show how the so called connectivity measure performs on a real DTI image with three different interpolation methods. Secondly, we introduce a new vector field on DTI images, that points out the locally most coherent direction for fiber tracking, and we illustrate it on bundles of tracked fibers. Thirdly, we introduce an inhomogeneity- (edge-, crossing-) detector for symmetric positive matrix valued images, including DTI images. One possible application is segmentation of diffusion tensor fields.
Cite
Text
Astola and Florack. "Sticky Vector Fields, and Other Geometric Measures on Diffusion Tensor Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008. doi:10.1109/CVPRW.2008.4562997Markdown
[Astola and Florack. "Sticky Vector Fields, and Other Geometric Measures on Diffusion Tensor Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008.](https://mlanthology.org/cvprw/2008/astola2008cvprw-sticky/) doi:10.1109/CVPRW.2008.4562997BibTeX
@inproceedings{astola2008cvprw-sticky,
title = {{Sticky Vector Fields, and Other Geometric Measures on Diffusion Tensor Images}},
author = {Astola, Laura and Florack, Luc},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2008},
pages = {1-7},
doi = {10.1109/CVPRW.2008.4562997},
url = {https://mlanthology.org/cvprw/2008/astola2008cvprw-sticky/}
}