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A Phase Field Approach to Limited-angle Tomographic Reconstruction

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The tomography of an object with limited angle can be addressed through Iterative Reconstruction Reprojection (IRR) procedure, where in a standard reconstruction procedure is used together with a "filtering" of the image at each iteration. It is here proposed to use as a filter a phase-field — or Cahn-Hilliard — regularization interlaced with a filtered back-projection reconstruction. This reconstruction procedure is tested on a cone-beam tomography of a 3D woven ceramic composite material, and is shown to retrieve a reconstructed volume with very low artifacts in spite of a large missing angle interval (up to 28%).
Wydawca
Rocznik
Strony
203--219
Opis fizyczny
Bibliogr. 23 poz., rys., wykr.
Twórcy
  • Laboratoire des Composites Thermo-Structuraux (LCTS), CNRS, CEA, SAFRAN, Univ. de Bordeaux, Pessac, France
  • Laboratoire de Mécanique et Technologie (LMT), ENS Paris-Saclay, CNRS, Univ. Paris-Saclay, Cachan Cedex, France
autor
  • Laboratoire des Composites Thermo-Structuraux (LCTS), CNRS, CEA, SAFRAN, Univ. de Bordeaux, Pessac, France
  • Safran Ceramics, Mérignac, France
Bibliografia
  • [1] Kak AC, Slaney M. Principles of Computerized Tomographic Imaging. Society of Industrial and Applied Mathematics, 2001. 2nd Edition. ISBN: 9780898714944.
  • [2] Hayashida M, Maiac M. Practical electron tomography guide: Recent progress and future opportunities. Micron, 2016. 91:49-74. doi:10.1016/j.micron.2016.09.010.
  • [3] Siltanen S, Kolehmainen V, Järvenpää S, Kaipio JP, Koistinen P, Lassas M, Pirttil J, Somersalo E. Statistical inversion for medical x-ray tomography with few radiographs: I. General theory. Phys. Med. Biol., 2003. 48(10):1437-1463. doi:10.1088/0031-9155/48/10/314.
  • [4] Nassi M, Brody WR, Medoff BP, Macovsky A. Iterative Reconstruction-Reprojection: An algorithm for limited data cardiac-computed tomography. IEEE Trans. Biomed. Eng., 1982. BME-29(5)(5):331-341. doi:10.1109/TBME.1982.324900.
  • [5] Medoff BP, Brody WR, Nassi M, Macovsky A. Iterative convolution backprojection algorithms for image reconstruction from limited data. J. Opt. Soc. Am., 1983. 73(11):1493-1500. doi:10.1364/JOSA.73.001493.
  • [6] Heffernan PB, Robb RA. Image reconstruction from incomplete projection data: iterative reconstruction reprojection techniques. IEEE Trans. Biomed. Eng., 1982. BME-30(12):838-841. doi:10.1109/TBME.1983.325089.
  • [7] Riddell C, Bourguignon MH, Bendriem B, Frouin V, Syrota A. Iterative Reprojection Reconstruction algorithm with attenuation correction applied to truncated projections in SPECT. In: 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, volume 5. 1992 pp. 1818-1820. doi:10.1109/IEMBS.1992.5762055.
  • [8] Ollinger JM. Iterative reconstruction-reprojection and the expectation-maximization algorithm. IEEE Trans. Med. Imag., 1990. 9(1):94-98. doi:10.1109/42.52986.
  • [9] Duan X, Zhang L, Xing Y, Chen Z, Cheng J. Few-View Projection Reconstruction With an Iterative Reconstruction-Reprojection Algorithm and TV Constraint. IEEE Trans. Nucl. Sci., 2009. 56(3):1377-1382. doi:10.1109/TNS.2008.2009990.
  • [10] Candès EJ, Romberg JK. Signal recovery from random projections. In: Computational Imaging III, volume 5674. International Society for Optics and Photonics, 2005 pp. 76-87. doi:10.1117/12.600722.
  • [11] Cahn JW, Hilliard JE. Free energy of a nonuniform system. I. Iterfacial free energy. J. Chem. Phys., 1958. 28(2):258-267. doi:10.1063/1.1744102.
  • [12] Allen SM, Cahn JW. A microscopic theory for antiphase boundary motion and its application to antiphase domain coarsening. Acta Metall., 1978. 27:1085-1095. URL https://doi.org/10.1016/0001-6160(79)90196-2.
  • [13] Li Y, Kim J. Multiphase image segmentation using phase-field model. Comput. Math. Appl., 2011. 62:737-745. URL https://doi.org/10.1016/j.camwa.2011.05.054.
  • [14] Naslain R. Design, preparation and properties of non-oxide CMCs for application in engines and nuclear reactors: an overview. Compos. Sci. Technol., 2004. 64:155-170. URL https://doi.org/10.1016/S0266-3538(03)00230-6.
  • [15] Cox BN, A BH, Begley M, Blacklock M, Do BC, Fast T, Naderi M, Novak M, Rajan VP, Rinaldi RG, Ritchie RO, Rossol MN, Shaw JH, Sudre O, Yang Q, Zok FW, Marshall DB. Stochastic virtual tests for high-temperature ceramic matrix composites. Annu. Rev. Mater. Res., 2014 pp. 479-529. URL https://doi.org/10.1146/annurev-matsci-122013-025024.
  • [16] Mazars V, Caty O, Couégnat G, Bourtef A, Roux S, Denneulin S, Pailhès J, Vignoles GL. Damage investigation and modeling of 3D woven ceramic matrix composites from X-ray tomography in-situ tensile tests. Acta Mater., 2017. 140:130-139. doi:10.1016/j.actamat.2017.08.034.
  • [17] Van Aarle W, Palenstijn WJ, De Beenhouwer J, Altantzis T, Bals S, Batenburg KJ, Sijbers J. The ASTRA Toolbox: a plateform for advanced algorithm development in electron tomography. Ultramicroscopy, 2015. 157:35-47. URL https://doi.org/10.1016/j.ultramic.2015.05.002.
  • [18] Van Aarle W, Palenstijn WJ, Cant J, Jassens E, Folkert B, Dabravolski A, De Beenhouwer J, Batenburg KJ, Sijbers J. Fast and flexible X-ray tomography using the ASTRA toolbox. J. Opt. Soc. Am., 2016. 24(22):25129-25147. URL https://doi.org/10.1364/OE.24.025129.
  • [19] Palenstijn WJ, Batenburg KJ, Sijbers J. Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs). J. Struct. Biol., 2011. 176:250-253. doi:10.1016/j.jsb.2011.07.017.
  • [20] Frese T, Bouman CA, Sauer K. Multiscale Bayesian Methods for Discrete Tomography, pp. 237-264. Birkhäuser Boston, Boston, MA. ISBN 978-1-4612-1568-4, 1999. doi:10.1007/978-1-4612-1568-4_10.
  • [21] Otsu N. A treshold selection method from gray-level histograms. IEEE Trans. Syst., Man, Cybern., 1979. SMC-9(1):62-66. doi:10.1109/TSMC.1979.4310076.
  • [22] Anderson DM, McFadden GB, Wheeler AA. Diffuse-interface methods in fluid mechanics. Annu. Rev. Fluid Mech., 1998. 30:139-165. URL https://doi.org/10.1146/annurev.fluid.30.1.139.
  • [23] Bertozzi AL, Esedoḡu S, Gilette A. Inpainting of binary images using the Cahn-Hilliard Equation. IEEE Trans. Image Process., 2007. 16(1):285-291. doi:10.1109/TIP.2006.887728
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-af2e3a6f-33ad-4e58-91ea-5bd35bfe511f
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