Abstract

Studying large deformations with a Riemannian approach has been an efficient point of view to generate metrics between deformable objects, and to provide accurate, non ambiguous and smooth matchings between images. In this paper, we study the geodesics of such large deformation diffeomorphisms, and more precisely, introduce a fundamental property that they satisfy, namely the conservation of momentum. This property allows us to generate and store complex deformations with the help of one initial "momentum" which serves as the initial state of a differential equation in the group of diffeomorphisms. Moreover, it is shown that this momentum can be also used for describing a deformation of given visual structures, like points, contours or images, and that, it has the same dimension as the described object, as a consequence of the normal momentum constraint we introduce.

Keywords

GeodesicProperty (philosophy)Momentum (technical analysis)Point (geometry)MathematicsConstraint (computer-aided design)Dimension (graph theory)Differential geometryComputer scienceMathematical analysisGeometryPure mathematics

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Publication Info

Year
2006
Type
article
Volume
24
Issue
2
Pages
209-228
Citations
363
Access
Closed

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363
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22
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282
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Cite This

Michael I. Miller, Alain Trouvé, Laurent Younès (2006). Geodesic Shooting for Computational Anatomy. Journal of Mathematical Imaging and Vision , 24 (2) , 209-228. https://doi.org/10.1007/s10851-005-3624-0

Identifiers

DOI
10.1007/s10851-005-3624-0
PMID
20613972
PMCID
PMC2897162

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Data completeness: 81%