An entropy-based technique for nonrigid medical image alignment

Authors:
Mohammed Khader;A. Ben Hamza
Affiliations:
Concordia Institute for Information Systems Engineering, Concordia University, Montréal, QC, Canada;Concordia Institute for Information Systems Engineering, Concordia University, Montréal, QC, Canada
Venue:
IWCIA'11 Proceedings of the 14th international conference on Combinatorial image analysis
Year:
2011

Citing 5
Cited 0

Spatial transformation and registration of brain images using elastically deformable models

Computer Vision and Image Understanding
Alignment by Maximization of Mutual Information

International Journal of Computer Vision
Fast Fluid Registration of Medical Images

VBC '96 Proceedings of the 4th International Conference on Visualization in Biomedical Computing
Non-Rigid Multi-Modal Image Registration Using Cross-Cumulative Residual Entropy

International Journal of Computer Vision
Deformable templates using large deformation kinematics

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose a nonrigid image registration technique by minimizing an information-theoretic measure using the quasi-Newton method as an optimization scheme and a cubic B-spline for modeling the nonrigid deformation field between the reference and target 3D image pairs. Experimental results are provided to demonstrate the registration accuracy of the proposed approach. The feasibility of our method is demonstrated on a 3D magnetic resonance data volume.