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Evolutions equations in computational anatomy
- Source :
- NeuroImage. 45
- Publication Year :
- 2008
-
Abstract
- One of the main purposes in computational anatomy is the measurement and statistical study of anatomical variations in organs, notably in the brain or the heart. Over the last decade, our group has progressively developed several approaches for this problem, all related to the Riemannian geometry of groups of diffeomorphisms and the shape spaces on which these groups act. Several important shape evolution equations that are now used routinely in applications have emerged over time. Our goal in this paper is to provide an overview of these equations, placing them in their theoretical context, and giving examples of applications in which they can be used. We introduce the required theoretical background before discussing several classes of equations of increasingly complexity. These equations include energy minimizing evolutions deriving from Riemannian gradient descent, geodesics, parallel transport and Jacobi fields.
- Subjects :
- Mathematical optimization
Large deformation diffeomorphic metric mapping
Parallel transport
Geodesic
Group (mathematics)
Cognitive Neuroscience
Brain
Computational Biology
Context (language use)
Heart
Riemannian geometry
Models, Theoretical
Computational anatomy
Article
symbols.namesake
Neurology
symbols
Calculus
Animals
Humans
Anatomy
Gradient descent
Algorithms
Mathematics
Subjects
Details
- ISSN :
- 10959572
- Volume :
- 45
- Database :
- OpenAIRE
- Journal :
- NeuroImage
- Accession number :
- edsair.doi.dedup.....da61c973b59c0732633157b2872a0186