A general PDE-framework for registration of contrast enhanced images.
This paper presents a general PDE-framework for registration of contrast enhanced images. The approach directly applies the idea of separating the contrast enhancement term from the images in the regularization terms. In our formulation, we stay consistent with existing non-parametric image registration techniques, however, we carry an additional contrast enhancement term throughout. A mathematically rigorous approach is pursued which can exploit various forms of regularization. In this paper, our experiments are built based on diffusion regularization for both contrast enhancement and the deformation field.
Ebrahimi
Mehran
M
Department of Medical Biophysics, University of Toronto, Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada. mehran.ebrahimi@sri.utoronto.ca
Martel
Anne L
AL
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D003287:Contrast Media; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique
D003287:Contrast Media