A hierarchical approach to elastic registration based on mutual information

Abstract A hierarchical approach to elastic registration based on mutual information, in which the images are progressively subdivided, locally registered, and elastically interpolated, is presented. To improve the registration, a combination of prior and floating information on the joint probability is proposed. It is shown that such a combination increases the registration speed at the coarser levels in hierarchy, enables a registration of finer details, and provides additional guidance to the optimisation process. Besides, a threefold local registration consistency test and correction of shading were employed to increase the overall registration performance. The proposed hierarchical method for elastic registration was tested on an experimental database of 2D images of histochemically differently stained serial cross-sections of human skeletal muscle. The obtained results show that 95% of the images could be successfully registered. The inclusion of prior information is an important break through that may enable routine use of the mutual information cost function in a variety of 2D and 3D image registration algorithms in the future.

[1]  I. M. Yaglom,et al.  Geometric Transformations I , 1962 .

[2]  F. Bookstein.  Thin-plate splines and decomposition of deformation , 1989 .

[3]  Max A. Viergever,et al.  General multimodal elastic registration based on mutual information , 1998, Medical Imaging.

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

[5]  B Likar,et al.  Automatic extraction of corresponding points for the registration of medical images. , 1999, Medical physics.

[6]  S. Terakawa.  Video Microscopy , 1985, Tanpakushitsu kakusan koso. Protein, nucleic acid, enzyme.

[7]  W. Eric L. Grimson,et al.  Multi-modal Volume Registration Using Joint Intensity Distributions , 1998, MICCAI.

[8]  Paul Suetens,et al.  Non-rigid Multimodal Image Registration Using Mutual Information , 1998, MICCAI.

[9]  J. Weaver,et al.  Multiresolution elastic image registration. , 1998, Medical physics.

[10]  Charles R. Meyer,et al.  Retrospective correction of intensity inhomogeneities in MRI , 1995, IEEE Trans. Medical Imaging.

[11]  Viergever,et al.  Retrospective shading correction based on entropy minimization , 2000, Journal of microscopy.

[12]  Paul A. Viola.  Alignment by maximisation of mutual information , 1993 .

[13]  Simon R. Arridge,et al.  A survey of hierarchical non-linear medical image registration , 1999, Pattern Recognit..

[14]  Lisa M. Brown,et al.  A survey of image registration techniques , 1992, CSUR.

[15]  Guy Marchal,et al.  Multimodality image registration by maximization of mutual information , 1997, IEEE Transactions on Medical Imaging.

[16]  David Applebaum.  Probability and information , 1996 .

[17]  Boštjan Likar,et al.  Registration of serial transverse sections of muscle fibers. , 1999 .

[18]  G. Marchal,et al.  Multi-modal volume registration by maximization of mutual information , 1997 .

[19]  Charles R. Meyer,et al.  Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations , 1997, Medical Image Anal..

[20]  D J Hawkes,et al.  Algorithms for radiological image registration and their clinical application , 1998, Journal of anatomy.

[21]  Max A. Viergever,et al.  Interpolation Artefacts in Mutual Information-Based Image Registration , 2000, Comput. Vis. Image Underst..

[22]  Colin Studholme,et al.  An overlap invariant entropy measure of 3D medical image alignment , 1999, Pattern Recognit..