An information theoretic approach for non-rigid image registration using voxel class probabilities

Medical Image Analysis

Volumn 10, Issue 3 SPEC. ISS., 2006, Pages 413-431

  D'Agostino, Emiliano ^a   Maes, Frederik ^a   Vandermeulen, Dirk ^a   Suetens, Paul ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

Mutual information; Non rigid registration; Tissue segmentation; Viscous fluid model

Indexed keywords

IMAGE SEGMENTATION; MATHEMATICAL MODELS; PATTERN MATCHING; PROBABILITY DISTRIBUTIONS;

IMAGE REGISTRATION; MUTUAL INFORMATION; NON-RIGID REGISTRATION; TISSUE SEGEMNTATION; VISCOUS FLUID MODEL;

MEDICAL IMAGING;

ANALYTIC METHOD; ARTICLE; ATLAS; BRAIN TISSUE; CONTROLLED STUDY; ENTROPY; FORCE; IMAGE ANALYSIS; IMAGE PROCESSING; INFORMATION PROCESSING; MATHEMATICAL COMPUTING; NUCLEAR MAGNETIC RESONANCE; PRIORITY JOURNAL; PROBABILITY; THEORETICAL MODEL;

EID: 33645898349     PISSN: 13618415     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.media.2005.03.004     Document Type: Article

References (22)

1. Ashburner, J., Friston, K., 2004. Segmentation by integrating intensity-based classification and template matching. In: Bookheimer, S., Poline, J., Gulyás, B. (Eds.), Human Brain Mapping (HBM'04).
2. Cocosco C., Kollokian V., Kwan R.-S., and Evans A. Brainweb: Online interface to a 3D MRI simulated brain database. NeuroImage 5 4, part 2/4 (1997) S425. http://www.bic.mni.mcgill.ca/brainweb/ Available from:
3. Cover T., and Thomas J. Elements of information theory (1991), Wiley, New York, N.Y., USA
4. D'Agostino E., Maes F., Vandermeulen D., and Suetens P. A viscous fluid model for multimodal non-rigid image registration using mutual information. Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Lecture Notes in Computer Science vol. 2488 (2002), Springer, Berlin, Tokyo, Japan 541-548
5. D'Agostino E., Maes F., Vandermeulen D., and Suetens P. A viscous fluid model for multimodal non-rigid image registration using mutual information. Medical Image Analysis 7 4 (2003) 565-575
6. D'Agostino E., Modersitzki J., Maes F., Vandermeulen D., Fischer B., and Suetens P. Free-form registration using mutual information and curvature regularization. In: Gee J., Maintz J., and Vannier M. (Eds). Proceedings of the second international Workshop on Biomedical Image Registration (WBIR 2003). Lecture Notes in Computer Science vol. 2717 (2003), Springer, Berlin, Philadelphia 11-20
7. Hermosillo G., Chef d'Hotel C., and Faugeras O. Variational methods for multimodal image matching. International Journal of Computer Vision 50 3 (2002) 329-343
8. Likar B., and Pernuš F. A hierarchical approach to elastic registration based on mutual information. Image and Vision Computing 19 1-2 (2001) 33-44
9. Maes, F., 1998. Segmentation and registration of multimodal medical images: from theory, implementation and validation to a useful tool in clinical pactice. Ph.D. Thesis, KU Leuven, Department of Electrical Engineering (ESAT/PSI), Leuven, Belgium.
10. Maes F., Collignon A., Vandermeulen D., Marchal G., and Suetens P. Multi-modality image registration by maximization of mutual information. IEEE Transactions on Medical Imaging 16 2 (1997) 187-198
11. Maes F., Vandermeulen D., and Suetens P. Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information. Medical Image Analysis 3 4 (1999) 373-386
12. Maes F., Vandermeulen D., and Suetens P. Medical image registration using mutual information. Proceedings of the IEEE - Special Issue on: Emerging Medical Imaging Technology 91 10 (2003) 1699-1722
13. Pluim J., Maintz J., and Viergever M. Interpolation artefacts in mutual information-based image registration. Computer Vision and Image Understanding 77 2 (2000) 211-232
14. Rogelj P., Kovačič S., and Gee J.C. Point similarity measures for non-rigid registration of multi-modal data. Computer Vision and Image Understanding 92 1 (2003) 112-140
15. Rohlfing Jr. T.R.B.C.M., and Menzel R. Bee brains, b-splines and computational democracy: generating an average shape atlas. IEEE workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01). Lecture Notes in Computer Science (2001), IEEE Computer Society, Kauai, Hawaii 187-194
16. Rueckert D., Sonoda L., Hayes C., Hill D., Leach M., and Hawkes D. Nonrigid registration using free-form deformations: application to breast MR images. IEEE Transactions on Medical Imaging 18 8 (1999) 712-721
17. Studholme C., Hill D., and Hawkes D. An overlap invariant entropy measure of 3d medical image alignment. Pattern Recognition 32 1 (1999) 71-86
18. Van Leemput K., Maes F., Vandermeulen D., and Suetens P. Automatedmodel-based bias field correction of MR images of the brain. IEEE Transactions on Medical Imaging 18 10 (1999) 885-896
19. Van Leemput K., Maes F., Vandermeulen D., and Suetens P. Automated model-based tissue classification of MR images of the brain. IEEETransactions on Medical Imaging 18 10 (1999) 897-908
20. Van Leemput K., Maes F., Vandermeulen D., Colchester A., and Suetens P. Automated segmentation of multiple sclerosis lesions by model outlier detection. IEEE Transactions on Medical Imaging 20 8 (2001) 677-688
21. Warfield S.K., Knaus M., Jolesz F.A., and Kikinis R. Adaptive, template moderate, spatially varying statistical classification. Medical Image Analysis 4 1 (2000) 43-55
22. Wells III W., Viola P., Atsumi H., Nakajima S., and Kikinis R. Multi-modal volume registration by maximization of mutual information. Medical Image Analysis 1 1 (1996) 35-51