Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-20T11:41:03.276Z Has data issue: false hasContentIssue false

A global stability estimate for the photo-acoustic inverse problem in layered media

Published online by Cambridge University Press:  17 May 2018

KUI REN
Affiliation:
Department of Mathematics and Institute of Computational Engineering and Sciences (ICES), The University of Texas, Austin, TX 78712, USA email: [email protected]
FAOUZI TRIKI
Affiliation:
Laboratoire Jean Kuntzmann, UMR CNRS 5224, Université Grenoble-Alpes, 700 Avenue Centrale, 38401 Saint-Martin-d'Hères, France email: [email protected]

Abstract

This paper is concerned with the stability issue in determining absorption and diffusion coefficients in photoacoustic imaging. Assuming that the medium is layered and the acoustic wave speed is known, we derive global Hölder stability estimates of the photoacoustic inversion. These results show that the reconstruction is stable in the region close to the optical illumination source, and deteriorate exponentially far away. Several experimental pointed out that the resolution depth of the photoacoustic modality is about tens of millimeters. Our stability estimates confirm these observations and give a rigorous quantification of this depth resolution.

MSC classification

Type
Papers
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

The research of FT was supported in part by grant LabEx PERSYVAL-Lab (ANR-11-LABX-0025-01) and grant ANR-17-CE40-0029 of the French National Research Agency ANR (project MultiOnde).

References

[1] Adams, R. A. & Fournier, J. F. (2003) Sobolev Spaces, 2nd ed., Academic Press.Google Scholar
[2] Agranovsky, M., Kuchment, P. & Kunyansky, L. (2009) On reconstruction formulas and algorithms for the thermoacoustic tomography. In: Wang, L. V. (editor), Photoacoustic Imaging and Spectroscopy, CRC Press, pp. 89101.Google Scholar
[3] Agranovsky, M. & Quinto, E. T. (1996) Injectivity sets for the Radon transform over circles and complete systems of radial functions. J. Funct. Anal. 139, 383414.Google Scholar
[4] Ammari, H., Bossy, E., Jugnon, V. & Kang, H. (2010) Mathematical modelling in photo-acoustic imaging of small absorbers. SIAM Rev. 52, 677695.Google Scholar
[5] Ammari, H., Bretin, E., Jugnon, V. & Wahab, A. (2012) Photo-acoustic imaging for attenuating acoustic media. In: Ammari, H. (editor), Mathematical Modeling in Biomedical Imaging II, Vol. 2035 of Lecture Notes in Mathematics, Springer-Verlag, pp. 5380.Google Scholar
[6] Ammari, H., Bretin, E., Garnier, J. & Jugnon, V. (2012) Coherent interferometry algorithms for photoacoustic imaging. SIAM J. Numer. Anal. 50, 22592280.Google Scholar
[7] Ammari, H., Kang, H. & Kim, S. (2012) Sharp estimates for Neumann functions and applications to quantitative photo-acoustic imaging in inhomogeneous media. J. Differ. Equ. 253, 4172.Google Scholar
[8] Ammari, K. & Choulli, M. (2017) Logarithmic stability in determining a boundary coefficient in an IBVP for the wave equation. Dynamics of PDE 14 (1) 3345.Google Scholar
[9] Ammari, K., Choulli, M. & Triki, F. (2016) Hölder stability in determining the potential and the damping coefficient in a wave equation. arXiv:1609.06102.Google Scholar
[10] Ammari, K., Choulli, M. & Triki, F. (2016) Determining the potential in a wave equation without a geometric condition. Extension to the heat equation. Proc. Am. Math. Soc. 144 (10), 43814392.Google Scholar
[11] Arridge, S. R. (1999) Optical tomography in medical imaging. Inverse Probl. 15, R41R93.Google Scholar
[12] Bal, G. (2012) Hybrid inverse problems and internal functionals. In: Uhlmann, G. (editor), Inside Out: Inverse Problems and Applications, Vol. 60 of Mathematical Sciences Research Institute Publications, Cambridge University Press, pp. 325368.Google Scholar
[13] Bal, G. & Ren, K. (2011) Multi-source quantitative photoacoustic tomography in a diffusive regime. Inverse Probl. 27 (7), 075003.Google Scholar
[14] Bal, G. & Ren, K. (2011) Non-uniqueness result for a hybrid inverse problem. Contemp. Math. 559, 2938.Google Scholar
[15] Bal, G. & Schotland, J. C. (2010) Inverse scattering and acousto-optics imaging. Phys. Rev. Lett. 104, 043902.Google Scholar
[16] Bal, G. & Uhlmann, G. (2010) Inverse diffusion theory of photoacoustics. Inverse Probl. 26 (8), 085010.Google Scholar
[17] Bal, G. & Uhlmann, G. (2013) Reconstruction of coefficients in scalar second-order elliptic equations from knowledge of their solutions. Commun. Pure Appl. Math. 66 (10), 16291652.Google Scholar
[18] Bardos, C., Lebeau, G. & Rauch, J. (1992) Sharp sufficient conditions for the observation, control and stabilization of waves from the boundary. SIAM J. Cont. Optim. 30, 10241065.Google Scholar
[19] Burgholzer, P., Matt, G. J., Haltmeier, M. & Paltauf, G. (2007) Exact and approximative imaging methods for photoacoustic tomography using an arbitrary detection surface. Phys. Rev. E 75, 046706.Google Scholar
[20] Burq, N. (1998) Contrôle de l'équation des ondes dans des ouverts comportant des coins. Bulletin de la S.M.F. 126, 601637.Google Scholar
[21] Cox, B. T., Arridge, S. R. & Beard, P. C. (2007) Photoacoustic tomography with a limited- aperture planar sensor and a reverberant cavity. Inverse Probl. 23, S95S112.Google Scholar
[22] Fink, M. & Tanter, M. (2010) Multiwave imaging and super resolution. Phys. Today 63, 2833.Google Scholar
[23] Finch, D., Haltmeier, M. & Rakesh, (2007) Inversion of spherical means and the wave equation in even dimensions. SIAM J. Appl. Math. 68, 392412.Google Scholar
[24] Grisvard, P. (1985) Elliptic Problems in Nonsmooth Domains, Pitman Publishing Inc.Google Scholar
[25] Haltmeier, M. (2011) A mollification approach for inverting the spherical mean Radon transform. SIAM J. Appl. Math. 71, 16371652.Google Scholar
[26] Haltmeier, M., Schuster, T. & Scherzer, O. (2005) Filtered backprojection for thermoacoustic computed tomography in spherical geometry. Math. Methods Appl. Sci. 28, 19191937.Google Scholar
[27] Hristova, Y. (2009) Time reversal in thermoacoustic tomography—An error estimate. Inverse Probl. 25, 055008.Google Scholar
[28] Hristova, Y., Kuchment, P. & Nguyen, L. (2008) Reconstruction and time reversal in thermoacoustic tomography in acoustically homogeneous and inhomogeneous media. Inverse Probl. 24, 055006.Google Scholar
[29] Isakov, V. (1998) Inverse problems for partial differential equations. Appl. Math. Sci. 127, Springer, New York.Google Scholar
[30] Kirsch, A. & Scherzer, O. (2013) Simultaneous reconstructions of absorption density and wave speed with photoacoustic measurements. SIAM J. Appl. Math. 72, 15081523.Google Scholar
[31] Kuchment, P. & Kunyansky, L. (2008) Mathematics of thermoacoustic tomography. Eur. J. Appl. Math. 19, 191224.Google Scholar
[32] Kuchment, P. & Kunyansky, L. (2010) Mathematics of thermoacoustic and photoacoustic tomography. In: Scherzer, O. (editor), Handbook of Mathematical Methods in Imaging, Springer-Verlag, pp. 817866.Google Scholar
[33] Kunyansky, L. (2008) Thermoacoustic tomography with detectors on an open curve: An efficient reconstruction algorithm. Inverse Probl. 24, 055021.Google Scholar
[34] Lions, J.-L. (1998) Contrôlabilité Exacte, Perturbations et Stabilisation de Systèmes Distribués, Vol. 1–2, Masson, Paris.Google Scholar
[35] Lions, J. L. & Magenes, E. (1972) Non-homogeneous Boundary Values Problems and Applications I, Springer-Verlag, Berlin, Heidelberg.Google Scholar
[36] Li, C. & Wang, L. (2009) Photoacoustic tomography and sensing in biomedicine. Phys. Med. Biol. 54, R59R97.Google Scholar
[37] McLean, W. (2000) Strongly Elliptic Systems and Boundary Integral Equations, Cambridge University Press.Google Scholar
[38] Mamonov, A. V. & Ren, K. (2014) Quantitative photoacoustic imaging in radiative transport regime. Comm. Math. Sci. 12, 201234.Google Scholar
[39] Naetar, W. & Scherzer, O. (2014) Quantitative photoacoustic tomography with piecewise constant material parameters. SIAM J. Imaging Sci. 7, 17551774.Google Scholar
[40] Nguyen, L. V. (2009) A family of inversion formulas in thermoacoustic tomography. Inverse Probl. Imaging 3, 649675.Google Scholar
[41] Patch, S. K. & Scherzer, O. (2007) Photo- and thermo- acoustic imaging. Inverse Probl. 23, S1S10.Google Scholar
[42] Qian, J., Stefanov, P., Uhlmann, G. & Zhao, H. (2011) An efficient Neumann-series based algorithm for thermoacoustic and photoacoustic tomography with variable sound speed. SIAM J. Imaging Sci. 4, 850883.Google Scholar
[43] Ren, K., Gao, H. & Zhao, H. (2013) A hybrid reconstruction method for quantitative photoacoustic imaging. SIAM J. Imaging Sci. 6, 3255.Google Scholar
[44] Scherzer, O. (2010) Handbook of Mathematical Methods in Imaging, Springer-Verlag.Google Scholar
[45] Stefanov, P. & Uhlmann, G. (2009) Thermoacoustic tomography with variable sound speed. Inverse Probl. 25, 075011.Google Scholar
[46] Tittelfitz, J. (2012) Thermoacoustic tomography in elastic media. Inverse Probl. 28, 055004.Google Scholar
[47] Tucsnak, M. & Weiss, G. (2009) Observation and control for operator semigroups. In: Birkhauser Advanced Texts, Birkhauser Verlag, Basel.Google Scholar
[48] Wang, L. V. (2008) Prospects of photoacoustic tomography. Med. Phys. 35, 5758. [PubMed: 19175133]Google Scholar
[49] Wang, L. V. editor (2009) Photoacoustic Imaging and Spectroscopy, Taylor & Francis.Google Scholar
[50] Yamamoto, M. (1995) Stability, reconstruction formula and regularization for an inverse source hyperbolic problem by a control method. Inverse Probl. 11 (2), 481.Google Scholar
[51] Zuazua, E. (2001) Some results and open problems on the controllability of linear and semilinear heat equations. In: Carleman Estimates and Applications to Uniqueness and Control Theory (Cortona, 1999), Vol. 46 of Progress Non-linear Differential Equations Applications, Birkhaüser Boston, Boston, MA, pp. 191211.Google Scholar