Image registration methods in MRI

Advanced Image Processing in Magnetic Resonance Imaging

Volumn , Issue , 2005, Pages 189-221

  Positano, Vincenzo ^a  

^a INSTITUTE OF CLINICAL PHYSIOLOGY   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 77950118914     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Chapter

References (48)

1. Hajnal, J.V., Hill, D.L.G., and Hawkes, D.J. (2001). View of the future. in Hajnal, J.V., Hill, D.L.G., Hawkes, D.J., (Eds.), Medical Image Registration. Boca Raton, FL: CRC.
2. Hill, D.L.G., Batchelor, P.G., Holden, M., and Hawkes, D.J. (2001). Medical image registration. Phys. Med. Biol. 46: R1-R45.
3. Jenkinson, M. and Smith, S. (2001). The role of registration in functional magnetic resonance imaging. in Hajnal, J.V., Hill, D.L.G., and Hawkes, D.J., (Eds.), Medical Image Registration. Boca Raton, FL: CRC.
4. Ashburner, J. and Friston, K.J. (2000). Image registration. in Functional MRI, Moonen, C.T.W., Bandettini, P.A., (Eds.), Springer.
5. Pluim, J.P.W. and Fitzpatrick, J.M. (2003). Image registration. IEEE Trans. Med. Imaging 22(11): 1341-1343.
6. Brown, L. (1992). A survey of image registration techniques. ACM Comput. Surv. 24: 325-376.
7. Hill, D.L.G. and Batchelor, P. (2001). Registration methodology: concepts and algorithms. in Hajnal, J.V., Hill, D.L.G., and Hawkes, D.J., (Eds.), Medical Image Registration. Boca Raton, FL: CRC.
8. Roche, A., Pennec, X., Malandain, G., and Ayache, N. (2001). Rigid registration of 3-D ultrasound with MR images: A new approach combining intensity and gradient information. IEEE Trans. Med. Imaging 20: 1038-1049.
9. Pluim, J.P.W., Maintz, J.B.A., and Viergever, M.A. (2003). Mutual-information-based registration of medical images: a survey. IEEE Trans. Med. Imaging. 22(8): 986-1004.
10. Robb, R.A. (2000). Biomedic Imaging, Visualization and Analysis. Wiley-Liss, New York.
11. Santarelli, M.F., Positano, V., Michelassi, C., Lombardi, M., and Landini, L. (2003). Automated cardiac MR image segmentation: theory and measurement evaluation. Medical Eng. Phys. 25(2): 149-159.
12. Besl, P.J. and McKay, N.D. (1992). A method for registration of 3-D shapes. IEEE Transaction on Pattern Analysis and Machine Intelligence. 14(2): 239-256.
13. Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., and Suetens, P. (1997). Multimodality image registration by maximization of mutual information. IEEE Trans. Med. Imaging 16: 187-198.
14. Wells, W.M., III, Viola, P., Atsumi, H., Nakajima, S., and Kikinis, R. (1996). Multi-modal volume registration by maximization of mutual information. Med. Image Anal. 1: 35-51.
15. Studholme, C., Hill, D.L.G., and Hawkes, D. (1999). An overlap invariant entropy measure of 3-D medical image alignment. Pattern Recognit. 32: 71-86.
16. Grevera, G.J. and Udupa, J.K. (1998). An objective comparison of 3-D image interpolation methods. IEEE Trans. Med. Imaging 17(4).
17. Lehmann, T.M., Gonner, C., and Spitzer, K. (1999). Survey: interpolation methods in medical image processing. IEEE Trans. Med. Imaging 18(11): 1049-1075.
18. Thacker, N.A., Jackson, A., Moriarty, D., and Vokurka, B. (1999). Improved quality of re-sliced MR images using re-normalised Sinc interpolation. J Magn. Resonance Imaging 10(4): 582-588.
19. Pluim, J.P.W., Maintz, J.B.A., and Viergever, M.A. (2001). Mutual information matching in multiresolution contexts. Image Vis. Comput. 19(1): 45-52.
20. Bernon, J.L., Boudousq, V., Rohmer, J.F., Fourcade, M., Zanca, M., Rossi, M., and Mariano-Goulart, D. (2001). A comparative study of Powell's and downhill simplex algorithms for a fast multimodal surface matching in brain imaging. Comput. Med. Imaging Graph. 25: 287-297.
21. Powell, M.J.D. (1964). An efficient method of finding the minimum of a function of several variables without calculating derivatives. Comput. J. 7: 155-163.
22. Maes, F., Vandermeulen, D., and Suetens, P. (1999). Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information. Med. Image Anal. 3: 373-386.
23. Nelder, J.A. and Mead, R. (1965). A simplex method for function minimization. Comput. J. 7: 308-313.
24. Matsopoulos, G.K., Mouravliansky, N.A., Delibasis, K.K., and Nikita, K.S. (1999). Automatic retinal image registration scheme using global optimization techniques. IEEE Trans. Inform. Technol. Biomed. 3: 47-60.
25. Fogel, D.B. (2000). Evolutionary Computation. IEEE Press, New York.
26. Wachowiak, M.P. and Elmaghraby, A.S. (2001). The continuous tabu search as an optimizer for 2-D-to-3-D biomedical image registration. Lecture Notes in Computer Science, W. Niessen and M. Viergever, Eds. New York: Springer-Verlag, Proc. MICCAI 2001-2208, 1273-1274.
27. Wachowiak, M.P., Smolikova, R., Zheng, Y., Zurada, J.M., and Elmaghraby, A.S. (2004). An approach to multimodal biomedical image registration utilizing particle swarm optimization. IEEE Trans. on Evolutionary Computation 8(3): 289-301.
28. Press, W.H., Flannery, B.P., Teukolsky, S.A., and Vetterling, W.T. (1988). Numerical Recipes in C: The Art of Scientific Computing. Cambridge University Press, Cambridge.
29. Walters, H., Parker, L.R., Morgan, S.L., and Deming, S.N. (1999). Sequential Simplex Optimization. CRC Press, Boca Raton, FL.
30. Krinidis, S., Nikou, C., and Pitas, I. (2003). A global energy function for the alignment of serially acquired slices. IEEE Trans. on Information Technology in Biomedicine. 7(2): 108-113.
31. Boes, J.L. and Meyer, C.R. (1999). Multi-variate mutual information for registration. Medical Image Computing and Computer-Assisted Intervention. Taylor, C., Colchester, A., Eds., Lecture Notes in Computer Science, Springer-Verlag. 1679: 606-612.
32. Zhang, J. and Rangarajan, A. (2004). Affine image registration using a new information metric. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 1: 848-855.
33. Positano, V., Santarelli, M.F., and Landini, L. (2003). Automatic characterization of myocardial perfusion in contrast enhanced MRI. EURASIP J. Appl. Signal Process. 5: 413-422.
34. Talairach, J. and Tournoux, p. (1988). Coplanar stereotaxic atlas of the human brain. Thieme Medical, New York.
35. Freire, L., Roche, A., and Mangin, J.F. (2002). What is the best similarity measure for motion correction in f MRI time series? IEEE Trans. Med. Imaging 21(5): 470-484.
36. Friston, K.J., Ashburner, J., Frith, C.D., Poline, J.B., Heather, J.D., and Frackowiak, R.S.J. (1995). Spatial registration and normalization of images. Hum. Brain Mapp. 2: 165-189.
37. Woods, R.P, Cherry, S.R., and Mazziotta, J.C. (1992). Rapid automated algorithm for aligning and reslicing PET images. J. Comput. Assist. Tomogr. 16: 620-633.
38. Nikou, C., Heitz, F., Armspach, J.P, Namer, I.J., and Grucker, D. (1998). Registration of MR/MR and MR/SPECT brain images by fast stochastic optimization of robust voxel similarity measures. NeuroImage, 8: 30-43.
39. Roche, A., Malandain, G., Pennec, X., and Ayache, N. (1998). The correlation ratio as a new similarity measure for multimodal image registration, in Lecture Notes in Computer Science. Berlin, Germany: Springer-Verlag, Vol. 1496, Proc. MICCAI'98, pp. 1115-1124.
40. Friston, K.J., Williams, S., Howard, R., Franckowiak, R.S.J., and Turner, R. (1996). Movement-related effects in fMRI time-series. Magn. Reson. Med. 35: 346-355.
41. Ashburner, J. and Friston, K.J. (2000). Image Registration in Functional MRI, Moonen, C.T.W., Bandettini, P.A., Eds., Springer-Verlag, New York.
42. Collins, D.L. and Neelin, P. et al. (1994). Automatic 3-D intersubject registration of mr volumetric data in standardized talairach space. J. Comput. Assist. Tomogr. 18(2): 192-205.
43. Schwitter, J., Nanz, D., Kneifel, S. et al. (2001). Assessment of myocardial perfusion in coronary artery disease by magnetic resonance. Circulation 103: 2230-2235.
44. Vallee, J.P., Sostman, H.D., MacFall, J.R., Wheeler, T., Hedlund, L.W., Spritzer, C.E., and Coleman, R.E. (1997). MRI quantitative myocardial perfusion with compartmental analysis: a rest and stress study. Magn. Reson. Med. 38: 981-989.
45. Yang, X., Taeymans, Y., Carlier, P., Verstraeten, P., Brunfaut, K., and Cornelis, M. (1993). Computer- aided measurement of local myocardial perfusion in MRI. Computers in Cardiology. Proceedings. 20: 365-368.
46. Gerig, G., Kikinis, R., Kuoni, W., von Schulthess, G.K., and Kubler, O. (1991). Semi-automated ROI analysis in dynamic MR studies. Part I: images analysis tools for automatic correction of organ displacements. J. Comput. Assist. Tomogr. 15: 725-732.
47. Delzescaux, T., Frouin, F., De Cesare, A., Philipp-Foliguet, S., Zeboudj, R., Janier, M., Todd-Pokropek, A., and Herment, A. (2000). Adaptive and self-evaluating registration method for myocardial perfusion assessment. MAGMA 13(1): 28-39.
48. Bidaut, L.M. and Vallée, J.P. (2001). Automated registration of dynamic MR images for the quantification of myocardial perfusion. J. Magn. Reson. Imaging 13(4): 648-55.