Multi-modality image registration by maximization of mutual information

Mutual information of image intensities has been proposed as a new matching criterion for automated multi-modality image registration. In this paper the authors give experimental evidence of the power and the generality of the mutual information criterion by showing results for various applications involving CT, MR and PET images. The authors' results illustrate the large applicability of the approach and demonstrate its high suitability for routine use in clinical practice.

[1]  Chi Hau Chen,et al.  Statistical Pattern Recognition. , 1973 .

[2]  Colin Studholme,et al.  Voxel similarity measures for automated image registration , 1994, Other Conferences.

[3]  Max A. Viergever,et al.  Automatic registration of CT and MR brain images using correlation of geometrical features , 1995, IEEE Trans. Medical Imaging.

[4]  William H. Press,et al.  Numerical recipes , 1990 .

[5]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[6]  Yves Bizais,et al.  Registration of multimodality medical images using a region overlap criterion , 1992, CVGIP Graph. Model. Image Process..

[7]  John Y. Chiang,et al.  Coincident bit counting-a new criterion for image registration , 1993, IEEE Trans. Medical Imaging.

[8]  W A Kalender,et al.  A phantom for standardization and quality control in spinal bone mineral measurements by QCT and DXA: design considerations and specifications. , 1992, Medical Physics (Lancaster).

[9]  I. Vajda Theory of statistical inference and information , 1989 .

[10]  Gerald Q. Maguire,et al.  Comparison and evaluation of retrospective intermodality brain image registration techniques. , 1997, Journal of computer assisted tomography.

[11]  Max A. Viergever,et al.  Comparison of Feature-Based Matching of CT and MR Brain Images , 1995, CVRMed.

[12]  David J. Hawkes,et al.  A Strategy for Automated Multimodality Image Registration Incorporating Anatomical Knowledge and Imager Characteristics , 1993, IPMI.

[13]  J. Mazziotta,et al.  MRI‐PET Registration with Automated Algorithm , 1993, Journal of computer assisted tomography.

[14]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

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

[16]  Guy Marchal,et al.  Automatic image partitioning for generic object segmentation in medical images , 1995 .

[17]  Colin Studholme,et al.  Automated 3D Registration of Truncated MR and CT Images of the Head , 1995, BMVC.

[18]  G. Marchal,et al.  On the problem of geometric distortion in magnetic resonance images for stereotactic neurosurgery. , 1994, Magnetic resonance imaging.

[19]  Alain Venot,et al.  A new class of similarity measures for robust image registration , 1984, Comput. Vis. Graph. Image Process..

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

[21]  Benoit M. Dawant,et al.  Comparison and evaluation of retrospective intermodality image registration techniques , 1996, Medical Imaging.

[22]  Guy Marchal,et al.  3D Multi-Modality Medical Image Registration Using Feature Space Clustering , 1995, CVRMed.

[23]  Guy Marchal,et al.  An image registration based approach to assess the geometrical accuracy obtainable from spiral CT imaging the European Spine Phantom , 1995 .

[24]  M. Viergever,et al.  Medical image matching-a review with classification , 1993, IEEE Engineering in Medicine and Biology Magazine.

[25]  Paul F. Hemler,et al.  Grey value correlation techniques used for automatic matching of CT and MR brain and spine images , 1994, Other Conferences.

[26]  Max A. Viergever,et al.  Image fusion using geometrical features , 1992, Other Conferences.

[27]  William H. Press,et al.  Numerical Recipes in C, 2nd Edition , 1992 .

[28]  Rasika Rajapakshe,et al.  Pseudocorrelation: a fast, robust, absolute, grey-level image alignment algorithm. , 1994 .

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