Elements of information theory
Elements of information theory
Spatial transformation and registration of brain images using elastically deformable models
Computer Vision and Image Understanding
Spline-Based Image Registration
International Journal of Computer Vision
Diffeomorphisms Groups and Pattern Matching in Image Analysis
International Journal of Computer Vision
Hierarchical B-spline refinement
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Variational Methods for Multimodal Image Matching
International Journal of Computer Vision
Non-rigid Multimodal Image Registration Using Mutual Information
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Multi-modal Volume Registration Using Joint Intensity Distributions
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Nonrigid Registration of 3D Scalar, Vector and Tensor Medical Data
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Fast Fluid Registration of Medical Images
VBC '96 Proceedings of the 4th International Conference on Visualization in Biomedical Computing
A Level-Set Based Approach to Image Registration
MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
Alignment by maximization of mutual information
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Robust Multi-Sensor Image Alignment
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Non-rigid registration using distance functions
Computer Vision and Image Understanding - Special issue on nonrigid image registration
Computer Vision and Image Understanding - Special issue on nonrigid image registration
A New Joint Clustering and Diffeomorphism Estimation Algorithm for Non-Rigid Shape Matching
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 1 - Volume 01
A Robust Algorithm for Point Set Registration Using Mixture of Gaussians
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Learning based non-rigid multi-modal image registration using Kullback-Leibler divergence
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
A novel parametric method for non-rigid image registration
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
Transitive inverse-consistent manifold registration
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
Simultaneous nonrigid registration of multiple point sets and atlas construction
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Cumulative residual entropy: a new measure of information
IEEE Transactions on Information Theory
Deformable templates using large deformation kinematics
IEEE Transactions on Image Processing
Optimization of mutual information for multiresolution image registration
IEEE Transactions on Image Processing
On Cumulative Entropies and Lifetime Estimations
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part I: Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy
An improved ct to fluoroscopy registration algorithm for the kinematic analysis of knee joints
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Symmetric deformable image registration via optimization of information theoretic measures
Image and Vision Computing
WBIR'10 Proceedings of the 4th international conference on Biomedical image registration
An entropy-based technique for nonrigid medical image alignment
IWCIA'11 Proceedings of the 14th international conference on Combinatorial image analysis
Neuronal data analysis based on the empirical cumulative entropy
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I
Improving NCC-based direct visual tracking
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Conditional variance of differences: a robust similarity measure for matching and registration
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Adaptive on-line similarity measure for direct visual tracking
Image and Vision Computing
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In this paper we present a new approach for the non-rigid registration of multi-modality images. Our approach is based on an information theoretic measure called the cumulative residual entropy (CRE), which is a measure of entropy defined using cumulative distributions. Cross-CRE between two images to be registered is defined and maximized over the space of smooth and unknown non-rigid transformations. For efficient and robust computation of the non-rigid deformations, a tri-cubic B-spline based representation of the deformation function is used. The key strengths of combining CCRE with the tri-cubic B-spline representation in addressing the non-rigid registration problem are that, not only do we achieve the robustness due to the nature of the CCRE measure, we also achieve computational efficiency in estimating the non-rigid registration. The salient features of our algorithm are: (i) it accommodates images to be registered of varying contrast+brightness, (ii) faster convergence speed compared to other information theory-based measures used for non-rigid registration in literature, (iii) analytic computation of the gradient of CCRE with respect to the non-rigid registration parameters to achieve efficient and accurate registration, (iv) it is well suited for situations where the source and the target images have field of views with large non-overlapping regions. We demonstrate these strengths via experiments on synthesized and real image data.