FAIR.m

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 46 articles , 1 standard article )

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  1. Bellavia, S.; Donatelli, M.; Riccietti, Elisa: An inexact non stationary Tikhonov procedure for large-scale nonlinear ill-posed problems (2020)
  2. 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)
  3. Reshniak, Viktor; Trageser, Jeremy; Webster, Clayton G.: A nonlocal feature-driven exemplar-based approach for image inpainting (2020)
  4. Ruthotto, Lars; Haber, Eldad: Deep neural networks motivated by partial differential equations (2020)
  5. Scheufele, Klaudius; Subramanian, Shashank; Mang, Andreas; Biros, George; Mehl, Miriam: Image-driven biophysical tumor growth model calibration (2020)
  6. 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)
  7. Theljani, Anis; Chen, Ke: A Nash game based variational model for joint image intensity correction and registration to deal with varying illumination (2020)
  8. Thompson, Tony; Chen, Ke: An effective diffeomorphic model and its fast multigrid algorithm for registration of lung CT images (2020)
  9. Zhang, Daoping; Chen, Ke: 3D orientation-preserving variational models for accurate image registration (2020)
  10. Zhang, Jin: Constrained linear curvature image registration model and its numerical algorithm (2020)
  11. Alahyane, M.; Hakim, A.; Laghrib, A.; Raghay, S.: A lattice Boltzmann method applied to the fluid image registration (2019)
  12. Chen, Ke; Grapiglia, Geovani Nunes; Yuan, Jinyun; Zhang, Daoping: Improved optimization methods for image registration problems (2019)
  13. Mang, Andreas; Gholami, Amir; Davatzikos, Christos; Biros, George: CLAIRE: a distributed-memory solver for constrained large deformation diffeomorphic image registration (2019)
  14. Neumayer, Sebastian; Persch, Johannes; Steidl, Gabriele: Regularization of inverse problems via time discrete geodesics in image spaces (2019)
  15. Scheufele, Klaudius; Mang, Andreas; Gholami, Amir; Davatzikos, Christos; Biros, George; Mehl, Miriam: Coupling brain-tumor biophysical models and diffeomorphic image registration (2019)
  16. Theljani, Anis; Chen, Ke: An augmented Lagrangian method for solving a new variational model based on gradients similarity measures and high order regulariation for multimodality registration (2019)
  17. Alahyane, Mohamed; Hakim, Abdelilah; Laghrib, Amine; Raghay, Said: Fluid image registration using a finite volume scheme of the incompressible Navier Stokes equation (2018)
  18. Chen, Yangang; Wan, Justin W. L.: Numerical method for image registration model based on optimal mass transport (2018)
  19. Debroux, Noémie; Le Guyader, Carole: A joint segmentation/registration model based on a nonlocal characterization of weighted total variation and nonlocal shape descriptors (2018)
  20. Haber, Eldad; Ruthotto, Lars: Stable architectures for deep neural networks (2018)

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