Flows of diffeomorphisms for multimodal image registration

We present a theoretical and computational framework for nonrigid multimodal registration. We proceed by minimization of statistical similarity criteria (global and local) in a variational framework, and use the corresponding gradients to drive a flow of diffeomorphisms allowing large deformations. This flow is introduced through a new template propagation method, by composition of small displacements. Regularization is performed using fast filtering techniques. This approach yields robust matching algorithms offering a good computational efficiency. We apply this method to compensate distortions between EPI images (fMRI) and anatomical MRI volumes.

[1]  Alain Trouvé,et al.  Diffeomorphisms Groups and Pattern Matching in Image Analysis , 1998, International Journal of Computer Vision.

[2]  Michael I. Miller,et al.  Deformable templates using large deformation kinematics , 1996, IEEE Trans. Image Process..

[3]  G. M.,et al.  Partial Differential Equations I , 2023, Applied Mathematical Sciences.

[4]  Paul Dupuis,et al.  Variational problems on ows of di eomorphisms for image matching , 1998 .

[5]  U. Grenander,et al.  Computational anatomy: an emerging discipline , 1998 .

[6]  Rachid Deriche,et al.  Fast algorithms for low-level vision , 1988, [1988 Proceedings] 9th International Conference on Pattern Recognition.

[7]  Michael Unser,et al.  Unwarping of unidirectionally distorted EPI images , 2000, IEEE Transactions on Medical Imaging.

[8]  N. Ayache,et al.  Multimodal Image Registration by Maximization of the Correlation Ratio , 1998 .

[9]  Max A. Viergever,et al.  A survey of medical image registration , 1998, Medical Image Anal..

[10]  Michael I. Miller,et al.  Group Actions, Homeomorphisms, and Matching: A General Framework , 2004, International Journal of Computer Vision.

[11]  Morten Bro-Nielsen,et al.  Fast Fluid Registration of Medical Images , 1996, VBC.

[12]  O. Faugeras,et al.  A variational approach to multi-modal image matching , 2001, Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision.

[13]  Paul M. Thompson,et al.  The role of image registration in brain mapping , 2001, Image Vis. Comput..

[14]  Jerrold E. Marsden,et al.  Averaged Template Matching Equations , 2001, EMMCVPR.

[15]  Paul A. Viola,et al.  Multi-modal volume registration by maximization of mutual information , 1996, Medical Image Anal..

[16]  J. Marsden,et al.  Product formulas and numerical algorithms , 1978 .

[17]  Olivier D. Faugeras,et al.  Dense image matching with global and local statistical criteria: a variational approach , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.