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Riemannian Geometric Statistics in Medical Image Analysis
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| Autres auteurs : | , , |
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| Format : | Livre |
| Langue : | anglais |
| Titre complet : | Riemannian Geometric Statistics in Medical Image Analysis / edited by Xavier Pennec, Stefan Sommer and Tom Fletcher |
| Publié : |
San Diego :
Academic Press
, cop. 2020 |
| Description matérielle : | 1 vol. (XIX-614 p.) |
| Sujets : |
| Notes : | Part 1 Foundations of geometric statistics Chapter 1 Introduction to differential and Riemannian geometry Chapter 2 Statistics on manifolds Chapter 3 Manifold-valued image processing with SPD matrices Chapter 4 Riemannian geometry on shapes and diffeomorphisms Chapter 5 Beyond Riemannian geometry Part 2 Statistics on manifolds and shape spaces Chapter 6 Object shape representation via skeletal models (s-reps) and statistical analysis Chapter 7 Efficient recursive estimation of the Riemannian barycenter on the hypersphere and the special orthogonal group with applications Chapter 8 Statistics on stratified spaces Chapter 9 Bias on estimation in quotient space and correction methods Chapter 10 Probabilistic approaches to geometric statistics Chapter 11 On shape analysis of functional data Part 3 Deformations, diffeomorphisms and their applications Chapter 12 Fidelity metrics between curves and surfaces: currents, varifolds, and normal cycles Chapter 13 A discretize-optimize approach for LDDMM registration Chapter 14 Spatially adaptive metrics for diffeomorphic image matching in LDDMM Chapter 15 Low-dimensional shape analysis in the space of diffeomorphisms Chapter 16 Diffeomorphic density registration |
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| Bibliographie : | Réf. bibliogr. en fin de chapitre. Index |
| ISBN : | 0-12-814725-3 978-0-12-814725-2 9780128147269 |