DocumentCode
2116395
Title
Sticky vector fields, and other geometric measures on diffusion tensor images
Author
Astola, Laura ; Florack, Luc
Author_Institution
Dept. of Math. & Comput. Sci., Eindhoven Univ. of Technol., Eindhoven
fYear
2008
fDate
23-28 June 2008
Firstpage
1
Lastpage
7
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.
Keywords
diffusion; edge detection; geometry; interpolation; matrix algebra; tensors; vectors; connectivity measure; crossing detector; diffusion tensor fields segmentation; diffusion tensor imaging analysis; edge detector; fiber tractography; geometric measurement; inhomogeneity detector; interpolation methods; sticky vector fields; symmetric positive matrix valued images; Anisotropic magnetoresistance; Diffusion tensor imaging; Image analysis; Image edge detection; Image segmentation; Interpolation; Karhunen-Loeve transforms; Mathematics; Optical fiber testing; Tensile stress;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition Workshops, 2008. CVPRW '08. IEEE Computer Society Conference on
Conference_Location
Anchorage, AK
ISSN
2160-7508
Print_ISBN
978-1-4244-2339-2
Electronic_ISBN
2160-7508
Type
conf
DOI
10.1109/CVPRW.2008.4562997
Filename
4562997
Link To Document