FAIR stands for Flexible Algorithms for Image Registration and is a combination of a book about image registration and a software package written in MATLAB. Image registration is required whenever images taken at different times, from different viewpoints, and/or different sensors need to be compared, merged, or integrated. Is is also known as alignment, co-registration, fusion, optical flow, or warping and models the process of transforming data into a common reference frame.

References in zbMATH (referenced in 51 articles , 1 standard article )

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  1. Hernandez, Monica: Combining the band-limited parameterization and semi-Lagrangian Runge-Kutta integration for efficient PDE-constrained LDDMM (2021)
  2. Malte Brunn, Naveen Himthani, George Biros, Miriam Mehl, Andreas Mang: CLAIRE: Constrained Large Deformation Diffeomorphic Image Registration on Parallel Computing Architectures (2021) not zbMATH
  3. Marsland, Stephen; McLachlan, Robert I.; Zarre, Raziyeh: Analysing `simple’ image registrations (2021)
  4. Zhang, Daoping; Lui, Lok Ming: Topology-preserving 3D image segmentation based on hyperelastic regularization (2021)
  5. Bellavia, S.; Donatelli, M.; Riccietti, Elisa: An inexact non stationary Tikhonov procedure for large-scale nonlinear ill-posed problems (2020)
  6. Debroux, Noémie; Aston, John; Bonardi, Fabien; Forbes, Alistair; Guyader, Carole Le; Romanchikova, Marina; Schönlieb, Carola-Bibiane: A variational model dedicated to joint segmentation, registration, and atlas generation for shape analysis (2020)
  7. Lang, Lukas F.; Neumayer, Sebastian; Öktem, Ozan; Schönlieb, Carola-Bibiane: Template-based image reconstruction from sparse tomographic data (2020)
  8. Reshniak, Viktor; Trageser, Jeremy; Webster, Clayton G.: A nonlocal feature-driven exemplar-based approach for image inpainting (2020)
  9. Ruthotto, Lars; Haber, Eldad: Deep neural networks motivated by partial differential equations (2020)
  10. Scheufele, Klaudius; Subramanian, Shashank; Mang, Andreas; Biros, George; Mehl, Miriam: Image-driven biophysical tumor growth model calibration (2020)
  11. Sherina, Ekaterina; Krainz, Lisa; Hubmer, Simon; Drexler, Wolfgang; Scherzer, Otmar: Displacement field estimation from OCT images utilizing speckle information with applications in quantitative elastography (2020)
  12. Theljani, Anis; Chen, Ke: A Nash game based variational model for joint image intensity correction and registration to deal with varying illumination (2020)
  13. Thompson, Tony; Chen, Ke: An effective diffeomorphic model and its fast multigrid algorithm for registration of lung CT images (2020)
  14. Zhang, Daoping; Chen, Ke: 3D orientation-preserving variational models for accurate image registration (2020)
  15. Zhang, Jin: Constrained linear curvature image registration model and its numerical algorithm (2020)
  16. Alahyane, M.; Hakim, A.; Laghrib, A.; Raghay, S.: A lattice Boltzmann method applied to the fluid image registration (2019)
  17. Chen, Ke; Grapiglia, Geovani Nunes; Yuan, Jinyun; Zhang, Daoping: Improved optimization methods for image registration problems (2019)
  18. Mang, Andreas; Gholami, Amir; Davatzikos, Christos; Biros, George: CLAIRE: a distributed-memory solver for constrained large deformation diffeomorphic image registration (2019)
  19. Neumayer, Sebastian; Persch, Johannes; Steidl, Gabriele: Regularization of inverse problems via time discrete geodesics in image spaces (2019)
  20. Scheufele, Klaudius; Mang, Andreas; Gholami, Amir; Davatzikos, Christos; Biros, George; Mehl, Miriam: Coupling brain-tumor biophysical models and diffeomorphic image registration (2019)

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