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Tomographic Reconstruction from a Few Views: A Multi-Marginal Optimal Transport Approach

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Abstract

In this article, we focus on tomographic reconstruction. The problem is to determine the shape of the interior interface using a tomographic approach while very few X-ray radiographs are performed. We use a multi-marginal optimal transport approach. Preliminary numerical results are presented.

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References

  1. Agueh, M., Carlier, G.: Barycenters in the Wasserstein space. SIAM J. Math. Anal. 43(2), 904–924 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  2. Abraham, R., Bergounioux, M., Trélat, E.: A penalization approach for tomographic reconstruction of binary axially symmetric objects. Appl. Math. Optim. 58, 345–371 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  3. Batenburg, K.J.: Reconstructing binary images from discrete X-rays, Technical report, Leiden University (2004)

  4. Batenburg, K.J.: A Network Flow Algorithm for Binary Image Reconstruction from Few Projections, vol. 4245, pp. 6–97. Springer, Berlin (2006)

    MATH  Google Scholar 

  5. Bergounioux, M., Trélat, E.: A variational method using fractional order hilbert spaces for tomographic reconstruction of blurred and noised binary images. J. Funct. Anal. 259, 2296–2332 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  6. Benamou, J.-D., Carlier, G., Cuturi, M., Peyré, G., Nenna, L.: Iterative Bregman projections for regularized transportation problems. SIAM J. Sci. Comp. 37, A1111–A1138 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  7. Bonnotte, N.: Unidimensional and evolution methods for optimal transportation, PhD Thesis, University of Paris Sud Orsay. cvgmt.sns.it (2014)

  8. Carlier, G., Ekeland, I.: Matching for teams. Econ. Theory 42(2), 397–418 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  9. Dellacherie, C., Meyer, P.-A.: Probabilities and Potential, Mathematical Studies, vol. 29. North-Holland, Hermann (1978)

    MATH  Google Scholar 

  10. Dinten, J.-M.: Tomographie à partir d’un nombre limité de projections: régularisation par des champs markoviens, Ph.D. thesis, Université de Paris–Sud (1990)

  11. Ekeland, I., Temam, R.: Convex Analysis and Variational Problems. Classics in Mathematics. Society for Industrial and Applied Mathematics, Philadelphia (1999)

    Book  MATH  Google Scholar 

  12. Gangbo, W., Świȩch, A.: Optimal maps for the multidimensional Monge-Kantorovich problem. Comm. Pure Appl. Math. 51(1), 23–45 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  13. Herman, G.: Image Reconstruction from Projections: The Fundamentals of Computerized Tomograph. Academic Press, New York (1980)

    MATH  Google Scholar 

  14. Hstao, Y.L., Herman, G.T., Gabor, T.: A coordinate ascent approach to tomographic reconstruction of label images from a few projections. Discrete Appl. Math. 151, 184–197 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  15. Hstao, Y .L., Herman, G.T., Gabor, T.: Discrete tomography withj a very few views, using gibbs priors and a marginal posterior mode approach. Electron. Notes Discrete Math. 20, 399–418 (2005)

    Article  MATH  Google Scholar 

  16. Natterer, F.: The Mathematics of Computerized Tomography. SIAM, Philadelphia (2001)

    Book  MATH  Google Scholar 

  17. Natterer, F., Wübeling, F.: Mathematical Methods in Image Reconstruction. SIAM, Philadelphia (2001)

    Book  Google Scholar 

  18. Partouche-Sebban, D., Abraham, I.: Scintillateur pour dispositif d’imagerie, module scintillateur, dispositif d’imagerie avec un tel scintillateur et procédé de fabrication d’un scintillateur. French Patent No. 2922319 (2009)

  19. Partouche-Sebban, D., Abraham, I., Laurio, S., Missault, C.: Multi-mev flash radiography in shock physics experiments: specific assemblages of monolithic scintillating crystals for use in ccd-based imagers, X-ray optics and instrumentation, Article ID 156984, p. 9 (2010)

  20. Quinto, E.T.: Singularities of the x-ray transform and limited data tomography in \({\mathbb{R}} ^2\) and \({\mathbb{R}} ^3\). SIAM J. Math. Anal 24, 1215–1225 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  21. Rabin, J., Peyré, G., Delon, J., Bernot, M.: Wasserstein barycenter and its application to texture mixing. In: Scale Space and Variational Methods in Computer Vision, LNCS, vol. 6667, pp. 435-446, Springer (2012)

  22. Santambrogio, F.: Optimal Transport for Applied Mathematicians. Birkhäuser Verlag, Basel (2015)

    Book  MATH  Google Scholar 

  23. Villani, C.: Topics in Optimal Transportation, Graduate Studies in Mathematics, 58. American Mathematical Society, Providence (2003)

    Google Scholar 

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Abraham, I., Abraham, R., Bergounioux, M. et al. Tomographic Reconstruction from a Few Views: A Multi-Marginal Optimal Transport Approach. Appl Math Optim 75, 55–73 (2017). https://doi.org/10.1007/s00245-015-9323-3

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  • DOI: https://doi.org/10.1007/s00245-015-9323-3

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