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Path Descriptors for Geometric Graph Matching and Registration

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8814))

Abstract

Graph and tree-like structures such as blood vessels and neuronal networks are abundant in medical imaging. We present a method to calculate path descriptors in geometrical graphs, so that the similarity between paths in the graphs can be determined efficiently. We show experimentally that our descriptors are more discriminative than existing alternatives. We further describe how to match two geometric graphs using our path descriptors. Our main application is registering images for which standard techniques are inefficient, because the appearance of the images is too different, or there is not enough texture and no uniquely identifiable keypoints to be found. We show that our approach can register these images with better accuracy than previous methods.

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References

  1. Türetken, E., Benmansour, F., Fua, P.: Automated reconstruction of tree structures using path classifiers and mixed integer programming. In: IEEE ICCV, pp. 566–573 (2012)

    Google Scholar 

  2. Zitová, B., Flusser, J.: Image registration methods: a survey. Image and Vision Computing 21, 977–1000 (2003)

    Article  Google Scholar 

  3. Can, A., Stewart, C.V., Roysam, B., Tanenbaum, H.L.: A feature-based, robust, hierarchical algorithm for registering pairs of images of the curved human retina. IEEE Trans. on Pattern Analysis and Machine Intelligence 24, 347–364 (2002)

    Article  Google Scholar 

  4. Serradell, E., Głowacki, P., Kybic, J., Moreno-Noguer, F., Fua, P.: Robust non-rigid registration of 2D and 3D graphs. In: IEEE CVPR, pp. 996–1003 (2012)

    Google Scholar 

  5. Pinheiro, M.A., Sznitman, R., Serradell, E., Kybic, J., Moreno-Noguer, F., Fua, P.: Active testing search for point cloud matching. In: Gee, J.C., Joshi, S., Pohl, K.M., Wells, W.M., Zöllei, L. (eds.) IPMI 2013. LNCS, vol. 7917, pp. 572–583. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  6. Torr, P.H.S., Zisserman, A.: MLESAC: A new robust estimator with application to estimating image geometry. Computer Vision and Image Understanding 78, 138–156 (2000)

    Article  Google Scholar 

  7. Chum, O., Matas, J.: Matching with PROSAC - progressive sample consensus. In: IEEE CVPR, pp. 220–226 (2005)

    Google Scholar 

  8. Besl, P.J., McKay, N.D.: A method for registration of 3-D shapes. IEEE Trans. on Pattern Analysis and Machine Intelligence 14(2), 239–256 (1992)

    Article  Google Scholar 

  9. Myronenko, A., Song, X.: Point set registration: Coherent point drift. IEEE Trans. on Pattern Analysis and Machine Intelligence 32(12), 2262–2275 (2010)

    Article  Google Scholar 

  10. Leordeanu, M., Hebert, M., Sukthankar, R.: An integer projected fixed point method for graph matching and map inference. In: NIPS (2009)

    Google Scholar 

  11. Zaslavskiy, M., Bach, F., Vert, J.-P.: A path following algorithm for the graph matching problem. IEEE Trans. on Pattern Analysis and Machine Intelligence 31(12), 2227–2242 (2009)

    Article  Google Scholar 

  12. Serradell, E., Moreno-Noguer, F., Kybic, J., Fua, P.: Robust elastic 2D/3D geometric graph matching. In: SPIE Medical Imaging, vol. 8314(1), pp. 831408-1–831408-8 (2012)

    Google Scholar 

  13. Basri, R., Costa, L., Geiger, D., Jacobs, D.: Determining the similarity of deformable shapes. Vision Research 38, 135–143 (1998)

    Article  Google Scholar 

  14. Frenkel, M., Basri, R.: Curve matching using the fast marching method. In: Rangarajan, A., Figueiredo, M.A.T., Zerubia, J. (eds.) EMMCVPR 2003. LNCS, vol. 2683, pp. 35–51. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  15. Unser, M.: Splines: A perfect fit for medical imaging. Progress in Biomedical Optics and Imaging 3, 225–236 (2002)

    Google Scholar 

  16. Pajdla, T., Gool, L.V.: Matching of 3-D curves using semi-differential invariants. In: IEEE ICCV, pp. 390–395 (1995)

    Google Scholar 

  17. Cho, M., Lee, J., Lee, K.M.: Reweighted random walks for graph matching. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part V. LNCS, vol. 6315, pp. 492–505. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  18. Sahni, S.: Computationally related problems. SIAM Journal on Computing 3(4), 262–279 (1974)

    Article  MathSciNet  Google Scholar 

  19. Kuhn, H.W.: The Hungarian method for the assignment problem. Naval Research Logistics 2(1–2), 83–97 (1955)

    Article  Google Scholar 

  20. Deng, K., Tian, J., Zheng, J., Zhang, X., Dai, X., Xu, M.: Retinal fundus image registration via vascular structure graph matching. Journal of Biomedical Imaging (2010)

    Google Scholar 

  21. Holtmaat, A., Randall, J., Cane, M.: Optical imaging of structural and functional synaptic plasticity in vivo. European Journal of Pharmacology 719(1–3), 128–136 (2013)

    Article  Google Scholar 

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Correspondence to Miguel Amável Pinheiro .

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Pinheiro, M.A., Kybic, J. (2014). Path Descriptors for Geometric Graph Matching and Registration. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8814. Springer, Cham. https://doi.org/10.1007/978-3-319-11758-4_1

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  • DOI: https://doi.org/10.1007/978-3-319-11758-4_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11757-7

  • Online ISBN: 978-3-319-11758-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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