Multiresolution 3D Image Registration Using Hybrid Ant Colony Algorithm and Powells Method

Yang Fan; Zhang Han-ling

doi:10.3724/SP.J.1146.2005.01010

Volume 29 Issue 3

Jan. 2011

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Article Navigation > Journal of Electronics & Information Technology > 2007 > 29(3): 622-625

Yang Fan, Zhang Han-ling. Multiresolution 3D Image Registration Using Hybrid Ant Colony Algorithm and Powells Method[J]. Journal of Electronics & Information Technology, 2007, 29(3): 622-625. doi: 10.3724/SP.J.1146.2005.01010

Citation:

Yang Fan, Zhang Han-ling. Multiresolution 3D Image Registration Using Hybrid Ant Colony Algorithm and Powells Method[J]. Journal of Electronics & Information Technology, 2007, 29(3): 622-625. doi: 10.3724/SP.J.1146.2005.01010

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Multiresolution 3D Image Registration Using Hybrid Ant Colony Algorithm and Powells Method

doi: 10.3724/SP.J.1146.2005.01010

Received Date: 2005-08-16
Rev Recd Date: 2005-12-26
Publish Date: 2007-03-19

Abstract

Abstract

Image registration based on mutual information is of high accuracy and robustness. Hence, it has received much attention these years. Unfortunately, the mutual information function is generally not a smooth function but one containing many local maxima, which has a large influence on optimization. This paper proposes a registration method based on wavelet representation. In this method the mutual information is used as the similarity measure and a hybrid algorithm combined by ant colony algorithm and Powells method as the search technique. This method is applied to the 3D registration of CT and MR. Experiments shows that this registration method could efficiently restrain local maxima of mutual information function and the subvoxel accuracy can be achieved.

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References

[1] Maes F, Collignon A, and Vandermeulen D, et al.. Multimodality image registration by maximization of mutual information[J].IEEE Trans. on Medical Imaging.1997, 16(2):187-198 [2] Maes F, Vandermeulen D, and Suetens P. Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information[J].Medical Image Analysis.1999, 3(4):373-386 [3] Pluim J P W, Maintz J B A, and Viergever M A. Mutual information based registration of medical images: A survey[J].IEEE Trans. on Medical Imaging.2003, 22(8):986-1004 [4] Plattard D, Soret M, and Troccaz J, et al.. Patient set-up using portal images: 2D/2D image registration using mutual information[J].Computer Aided Surgery.2000, 5(4):246-262 [5] Jenkinson M and Smith S. A global optimization method for robust affine registration of brain images[J].Medical Image Analysis.2001, 5(2):143-156 [6] Wachowiak M P, Smolikova R, and Zheng Y. An approach to multimodal biomedical image registration utilizing particle swarm optimization[J].IEEE Trans. on Evolutionary Computation.2004, 8(3):289-301 [7] Wachowiak M P. Similarity metrics and optimization for multimodal biomedical image registration. [Dissertation], University of Louisville, 2003. [8] Studholme C, Hill D L G, and Hawkes D J. An overlap invariant entropy measure of 3D medical image alignment[J].Pattern Recognition.1999, 32(1):71-86 [9] 杨虎, 马斌荣, 任海萍等. 基于互信息的人脑图像配准研究. 中国医学物理学杂志, 2001, 18(2): 69-73. Yang Hu, Ma Bin-rong, and Ren Hai-ping. Human brain image registration using mutual information. Chinese Journal of Medical Physics, 2001, 18(2): 69-73. [10] 马良. 来自昆虫世界的寻优策略蚂蚁算法. 自然杂志, 1999, 21(3): 161-163. Ma Liang. Ant algorithm─optimization strategy from the insect colony. Chinese Journal of Nature, 1999, 21(3): 161-163. [11] Dorigo M, Maniezzo V, and Colorni A. Ant system: Optimization by a colony of cooperating agents[J].IEEE Trans. on Systems, Man, and Cybernetic-Part B.1996, 26(1):29-41

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