A Gauss-Newton approach to joint image registration and intensity correction.
We develop a new efficient numerical methodology for automated simultaneous registration and intensity correction of images. The approach separates the intensity correction term from the images being registered in a regularized expression. Our formulation is consistent with the existing non-parametric image registration techniques, however, an extra additive intensity correction term is carried throughout. An objective functional is formed for which the corresponding Hessian and Jacobian is computed and employed in a multi-level Gauss-Newton minimization approach. In this paper, our experiments are based on elastic regularization on the transformation and total variation on the intensity correction. Validations on dynamic contrast enhanced MR abdominal images for both real and simulated data verified the efficacy of the model. The pursued approach is flexible in which we can exploit various forms of regularization on the transformation and the intensity correction.
Faculty of Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario, Canada L1H 7K4. Electronic address: mehran.ebrahimi@uoit.ca.
Mehran
M
Ebrahimi
Anthony
A
Lausch
Anne L
AL
Martel
D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008962:Models, Theoretical
Image registration; Intensity correction; Inverse problems; Multi-level; Optimization