Log‐Euclidean metrics for fast and simple calculus on diffusion tensors
Institut national de recherche en sciences et technologies du numérique · Laboratoire d’Imagerie Biomédicale
Abstract
Diffusion tensor imaging (DT-MRI or DTI) is an emerging imaging modality whose importance has been growing considerably. However, the processing of this type of data (i.e., symmetric positive-definite matrices), called "tensors" here, has proved difficult in recent years. Usual Euclidean operations on matrices suffer from many defects on tensors, which have led to the use of many ad hoc methods. Recently, affine-invariant Riemannian metrics have been proposed as a rigorous and general framework in which these defects are corrected. These metrics have excellent theoretical properties and provide powerful processing tools, but also lead in practice to complex and slow algorithms. To remedy this limitation, a new…
Citation impact
- FWCI
- 34.01
- Percentile
- 100%
- References
- 35
Authors
4- VAVincent ArsignyCorresponding
Institut national de recherche en sciences et technologies du numérique
- PFPierre Fillard
Institut national de recherche en sciences et technologies du numérique, Laboratoire d’Imagerie Biomédicale
- XPXavier Pennec
Institut national de recherche en sciences et technologies du numérique, Laboratoire d’Imagerie Biomédicale
- NANicholas Ayache
Institut national de recherche en sciences et technologies du numérique, Laboratoire d’Imagerie Biomédicale
Topics & keywords
- Euclidean geometry
- Diffusion MRI
- Affine transformation
- Tensor (intrinsic definition)
- Euclidean distance
- Computation
- Euclidean space
- Mathematics