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Quasi-Conformal Hybrid Multi-modality Image Registration and its Application to Medical Image Fusion

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Advances in Visual Computing (ISVC 2015)

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Abstract

Fusion of images with same or different modalities has been conquering medical imaging field more rapidly due to the presence of highly accessible patients’ information in recent years. For example, cross platform non-rigid registration of CT with MRI images has found a significant role in different clinical application. In some instances labelling of anatomical features by medical experts are also involved to further improve the accuracy and authenticity of the registration. Being motivated by these, we propose a new algorithm to compute diffeomorphic hybrid multi-modality registration with large deformations. Our iterative scheme consists of mainly two steps. First, we obtain the optimal Beltrami coefficient corresponding to the diffeomorphic mapping that exactly superimposes the feature points. The second step detects the intensity difference in the framework of mutual information. A non-rigid deformation which minimizes the intensity difference is then obtained. Experiments have been carried out on both synthetic and real data. Results demonstrate the stability and efficacy of the proposed algorithm to obtain diffeomorphic image registration.

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References

  1. Heckbert, P.S.: Survey of texture mapping. IEEE Comput. Graphics Appl. 6, 56–67 (1986)

    Article  Google Scholar 

  2. Sotiras, A., Davatzikos, C., Paragios, N.: Deformable medical image registration: a survey. IEEE Trans. Med. Imaging 32, 1153–1190 (2013)

    Article  Google Scholar 

  3. Zitova, B., Flusser, J.: Image registration methods: a survey. Image Vis. Comput. 21, 977–1000 (2003)

    Article  Google Scholar 

  4. Bookstein, F.L.: Principal warps: thin-plate splines and the decomposition of deformations. IEEE Trans. Pattern Anal. Mach. Intell. 11, 567–585 (1989)

    Article  MATH  Google Scholar 

  5. Joshi, S.C., Miller, M.I.: Landmark matching via large deformation diffeomorphisms. IEEE Trans. Image Process. 9, 1357–1370 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  6. Vercauteren, T., Pennec, X., Perchant, A., Ayache, N.: Diffeomorphic demons: efficient non-parametric image registration. NeuroImage 45, S61–S72 (2009)

    Article  Google Scholar 

  7. Thirion, J.P.: Image matching as a diffusion process: an analogy with Maxwell’s demons. Med. Image Anal. 2, 243–260 (1998)

    Article  Google Scholar 

  8. Glocker, B., Sotiras, A., Komodakis, N., Paragios, N.: Deformable medical image registration: setting the state of the art with discrete methods. Annu. Rev. Biomed. Eng. 13, 219–244 (2011)

    Article  Google Scholar 

  9. Christensen, G.E., Johnson, H.J.: Consistent image registration. IEEE Trans. Med. Imaging 20, 568–582 (2001)

    Article  Google Scholar 

  10. Chanwimaluang, T., Fan, G., Fransen, S.R.: Hybrid retinal image registration. IEEE Trans. Inf. Technol. Biomed. 10, 129–142 (2006)

    Article  Google Scholar 

  11. James, A., Dasarathy, B.: Medical image fusion: a survey of the state of the art. Inf. Fusion 19, 4–19 (2014)

    Article  Google Scholar 

  12. Li, H., Manjunath, B., Mitra, S.: Multisensor image fusion using the wavelet transform. Graph. Models Image Process. 57, 235–245 (1995)

    Article  Google Scholar 

  13. Naidu, V., Raol, J.: Pixel-level image fusion using wavelets and principal component analysis. Def. Sci. J. 58, 338–352 (2008)

    Article  Google Scholar 

  14. Lam, K.C., Lui, L.M.: Landmark and intensity based registration with large deformations via quasi-conformal maps. SIAM J. Imaging Sci. 7, 2364–2392 (2014)

    Article  MATH  MathSciNet  Google Scholar 

  15. Gardiner, F.P., Lakic, N.: Quasiconformal TeichmĂĽller Theory. Mathematical Surveys and Monographs. American Mathematical Society, Providence (2000)

    Google Scholar 

  16. Kroon, D.: Multimodality non-rigid demon algorithm image registration. Robust Non-rigid Point Matching 14, 120–126 (2008)

    Google Scholar 

  17. Astala, K., Iwaniec, T., Martin, G.: Elliptic Partial Differential Equations and Quasiconformal Mappings in the Plane. Oxford Graduate Texts in Mathematics. Princeton University Press, Princeton (2008)

    Book  Google Scholar 

  18. Lui, L.M., Lam, K.C., Wong, T.W., Gu, X.F.: Texture map and video compression using Beltrami representation. SIAM J. Imaging Sci. 6, 1880–1902 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  19. Barzilai, J., Borwein, J.: Two-point step size gradient methods. IMA J. Numer. Anal. 8, 141–148 (1988)

    Article  MATH  MathSciNet  Google Scholar 

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Acknowledgements

This project is supported by HKRGC GRF (Project ID: 2130363 Reference: 402413)

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Correspondence to Ka Chun Lam .

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Lam, K.C., Lui, L.M. (2015). Quasi-Conformal Hybrid Multi-modality Image Registration and its Application to Medical Image Fusion. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9474. Springer, Cham. https://doi.org/10.1007/978-3-319-27857-5_72

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  • DOI: https://doi.org/10.1007/978-3-319-27857-5_72

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27856-8

  • Online ISBN: 978-3-319-27857-5

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