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 57 articles , 1 standard article )

Showing results 1 to 20 of 57.
Sorted by year (citations)

1 2 3 next

  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. Nie, Ziwei; Li, Chen; Liu, Hairong; Yang, Xiaoping: A variational model for deformable registration of uni-modal medical images with intensity biases (2021)
  5. Nie, Ziwei; Li, Chen; Liu, Hairong; Yang, Xiaoping: Deformable image registration based on functions of bounded generalized deformation (2021)
  6. Zhang, Daoping; Lui, Lok Ming: Topology-preserving 3D image segmentation based on hyperelastic regularization (2021)
  7. Zhang, Daoping; Tai, Xue-cheng; Lui, Lok Ming: Topology- and convexity-preserving image segmentation based on image registration (2021)
  8. Zhang, Daoping; Theljani, Anis; Chen, Ke: Multi-modality image registration models and efficient algorithms (2021)
  9. Zhang, Jianping; Li, Yanyan: Diffeomorphic image registration with an optimal control relaxation and its implementation (2021)
  10. Bellavia, S.; Donatelli, M.; Riccietti, Elisa: An inexact non stationary Tikhonov procedure for large-scale nonlinear ill-posed problems (2020)
  11. 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)
  12. Lang, Lukas F.; Neumayer, Sebastian; Öktem, Ozan; Schönlieb, Carola-Bibiane: Template-based image reconstruction from sparse tomographic data (2020)
  13. Reshniak, Viktor; Trageser, Jeremy; Webster, Clayton G.: A nonlocal feature-driven exemplar-based approach for image inpainting (2020)
  14. Ruthotto, Lars; Haber, Eldad: Deep neural networks motivated by partial differential equations (2020)
  15. Scheufele, Klaudius; Subramanian, Shashank; Mang, Andreas; Biros, George; Mehl, Miriam: Image-driven biophysical tumor growth model calibration (2020)
  16. 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)
  17. Theljani, Anis; Chen, Ke: A Nash game based variational model for joint image intensity correction and registration to deal with varying illumination (2020)
  18. Thompson, Tony; Chen, Ke: An effective diffeomorphic model and its fast multigrid algorithm for registration of lung CT images (2020)
  19. Zhang, Daoping; Chen, Ke: 3D orientation-preserving variational models for accurate image registration (2020)
  20. Zhang, Jin: Constrained linear curvature image registration model and its numerical algorithm (2020)

1 2 3 next