Abstract
The multiresolution approach is commonly used to speed up the mutual-information (MI) based registration process. Conventionally, a Gaussian pyramid is often used as a multiresolution representation. However, in multi-modal medical image registration, MI-based methods with Gaussian pyramid may suffer from the problem of short capture ranges especially at the lower resolution levels. This paper proposes a novel and straightforward multimodal image registration method based on wavelet representation, in which two matching criteria are used including sum of difference (SAD) for improving the registration robustness and MI for assuring the registration accuracy. Experimental results show that the proposed method obtains a longer capture range than the traditional MI-based Gaussian pyramid method meanwhile maintaining comparable accuracy.
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References
Hajnal, J., Hill, D., Hawkes, D. (eds.): Medical Image Registration, 1st edn. CRC Press, Boca Raton (2001)
Wells III, W.M., Viola, P., Atsumi, H., Nakajima, S., Kikinis, R.: Multi-modal volume registration by maximization of mutual information. Medical Image Analysis 1, 35–51 (1996)
Pluim, J.P.W., Maintz, J.B.A., Viergever, M.A.: Mutual-information-based registration of medical images: A survey. IEEE Trans. Medical Imaging 22, 986–1004 (2003)
Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., Suetens, P.: Multimodality image registration by maximization of mutual information. IEEE Trans. Med. Imag. 16, 187–198 (1997)
Pluim, J.P.W., Maintz, J.B.A., Viergever, M.A.: Mutual information matching in multiresolution contexts. Image and Vision Computing 19, 45–52 (2001)
lrani, M., Anandan, P.: Robust multi-sensor image alignment. In: Proc. DARPA Image Understanding Workshop, vol. 1, pp. 639–647 (1997)
Moigne, J.L., Campbell, W.J., Cromp, R.F.: An automated parallel image registration technique based on the correlation of wavelet features. IEEE Trans. Geoscience and Remote Sensing 40, 1849–1864 (2002)
Moon, P., Jager, G.: An investigation into the applicability of the wavelet transform to digital stereo image matching. Joint IEEE Communications and Signal Processing Society, 75–79 (1993)
Turcajova, R., Kautsky, J.: A hierarchical multiresolution technique for image registration. In: Proc. of SPIE Mathematical Imaging: Wavelet: Applications in Signal and Image Processing (1996)
Liu, J., Vemuri, B.C., Marroquin, J.L.: Local frequency representations for robust multimodal image registration. IEEE Trans. Medical imageing 21, 462–469 (2002)
Zhen, J., Yifeng, J., Jihong, Z.: Automatic registration algorithm based on wavelet transform. In: Proc. of International Conference on Signal Processing 2000, pp. 979–982 (2000)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice Hall, Englewood Cliffs (2002)
BrainWeb (Mcgill), http://www.bic.mni.mcgill.ca/brainweb/
Cocosco, C.A., Kollokian, V., Kwan, R.K., Evans, A.C.: Brainweb: Online interface to a 3d mri simulated brain database. In: Proceedings of 3rd International Conference on Functional Mapping of the Human Brain (1997)
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© 2004 Springer-Verlag Berlin Heidelberg
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Wu, J., Chung, A.C.S. (2004). Multimodal Brain Image Registration Based on Wavelet Transform Using SAD and MI. In: Yang, GZ., Jiang, TZ. (eds) Medical Imaging and Augmented Reality. MIAR 2004. Lecture Notes in Computer Science, vol 3150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28626-4_33
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DOI: https://doi.org/10.1007/978-3-540-28626-4_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22877-6
Online ISBN: 978-3-540-28626-4
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