The Large Deformation Diffeomorphic Metric Mapping (LDDMM) tool is an application which aims to assign metric distances on the space of anatomical images in Computational Anatomy thereby allowing for the direct comparison and quantization of morphometric changes in shapes. As part of these efforts the Center for Imaging Science at Johns Hopkins University developed techniques to not only compare images, but also to visualize the changes and differences.

References in zbMATH (referenced in 63 articles , 1 standard article )

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  1. Effland, Alexander; Rumpf, Martin; Schäfer, Florian: Image extrapolation for the time discrete metamorphosis model: existence and applications (2018)
  2. Gris, Barbara; Durrleman, Stanley; Trouvé, Alain: A sub-Riemannian modular framework for diffeomorphism-based analysis of shape ensembles (2018)
  3. Camassa, Roberto; Kuang, Dongyang; Lee, Long: A geodesic landmark shooting algorithm for template matching and its applications (2017)
  4. Charlier, B.; Charon, N.; Trouvé, A.: The fshape framework for the variability analysis of functional shapes (2017)
  5. Gerber, Samuel; Maggioni, Mauro: Multiscale strategies for computing optimal transport (2017)
  6. Arguillère, Sylvain; Trélat, Emmanuel; Trouvé, Alain; Younes, Laurent: Registration of multiple shapes using constrained optimal control (2016)
  7. Camassa, Roberto; Kuang, Dongyang; Lee, Long: Solitary waves and $N$-particle algorithms for a class of Euler-Poincaré equations (2016)
  8. Mittal, Rajat; Seo, Jung Hee; Vedula, Vijay; Choi, Young J.; Liu, Hang; Huang, H. Howie; Jain, Saurabh; Younes, Laurent; Abraham, Theodore; George, Richard T.: Computational modeling of cardiac hemodynamics: current status and future outlook (2016)
  9. Allassonnière, S.; Durrleman, S.; Kuhn, E.: Bayesian mixed effect atlas estimation with a diffeomorphic deformation model (2015)
  10. Allassonnière, Stéphanie; Kuhn, Estelle: Convergent stochastic expectation maximization algorithm with efficient sampling in high dimension. Application to deformable template model estimation (2015)
  11. Arguillère, Sylvain; Trélat, Emmanuel; Trouvé, Alain; Younes, Laurent: Shape deformation analysis from the optimal control viewpoint (2015)
  12. Bal, Gulce; Diebold, Julia; Chambers, Erin Wolf; Gasparovic, Ellen; Hu, Ruizhen; Leonard, Kathryn; Shaker, Matineh; Wenk, Carola: Skeleton-based recognition of shapes in images via longest path matching (2015)
  13. Berkels, B.; Effland, A.; Rumpf, M.: Time discrete geodesic paths in the space of images (2015)
  14. Bruveris, Martins; Holm, Darryl D.: Geometry of image registration: the diffeomorphism group and momentum maps (2015)
  15. Delfour, Michel C.: Metric spaces of shapes and geometries constructed from set parametrized functions (2015)
  16. Ozeré, Solène; Gout, Christian; Le Guyader, Carole: Joint segmentation/registration model by shape alignment via weighted total variation minimization and nonlinear elasticity (2015)
  17. Rumpf, Martin; Wirth, Benedikt: Variational methods in shape analysis (2015)
  18. Yang, Xianfeng; Li, Yonghui; Reutens, David; Jiang, Tianzi: Diffeomorphic metric landmark mapping using stationary velocity field parameterization (2015)
  19. Bauer, Martin; Bruveris, Martins; Michor, Peter W.: Overview of the geometries of shape spaces and diffeomorphism groups (2014)
  20. Charon, Nicolas; Trouvé, Alain: Functional currents: a new mathematical tool to model and analyse functional shapes (2014)

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