Landmark matching via large deformation diffeomorphisms on the sphere

DOI10.1023/B:JMIV.0000011326.88682.e5zbMath1366.94052OpenAlexW2094992004WikidataQ56624034 ScholiaQ56624034MaRDI QIDQ1425803

Marc Vaillant, Michael I. Miller, Joan Alexis Glaunès

Publication date: 18 March 2004

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1023/b:jmiv.0000011323.32914.f3

zbMATH Keywords

spherediffeomorphismslarge deformationsgeodesic distancebrain mappinglandmark matching

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Biomedical imaging and signal processing (92C55) Dynamical systems in biology (37N25) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Methods of global Riemannian geometry, including PDE methods; curvature restrictions (53C21)

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Landmark-matching transformation with large deformation via \(n\)-dimensional quasi-conformal maps ⋮ The Euler-Poincaré theory of metamorphosis ⋮ Geometry of Image Registration: The Diffeomorphism Group and Momentum Maps ⋮ Bayesian Mixed Effect Atlas Estimation with a Diffeomorphic Deformation Model ⋮ Landmark constrained genus zero surface conformal mapping and its application to brain mapping research ⋮ Optimization of surface registrations using Beltrami holomorphic flow ⋮ Gromov-Wasserstein distances and the metric approach to object matching ⋮ Statistical models for deformable templates in image and shape analysis ⋮ A Sub-Riemannian Modular Framework for Diffeomorphism-Based Analysis of Shape Ensembles ⋮ Statistical M-estimation and consistency in large deformable models for image warping ⋮ Registration of Multiple Shapes using Constrained Optimal Control ⋮ Overview of the geometries of shape spaces and diffeomorphism groups ⋮ A splitting method for diffeomorphism optimization problem using Beltrami coefficients

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