Inverse problems of experimental data interpretation in 3D ultrasound tomography
Authors
-
A.V. Goncharsky
-
V.A. Kubyshkin
-
S.Yu. Romanov
-
S.Yu. Seryozhnikov
Keywords:
ultrasound tomography
inverse problems
medical imaging
GPU cluster
Abstract
The inverse problem of 3D ultrasound tomography is considered in this paper as a nonlinear coefficient inverse problem for a hyperbolic equation. The employed mathematical model accurately describes the effects of ultrasound wave diffraction and absorption in inhomogeneous media. The velocity of acoustic waves inside the test sample is reconstructed as an unknown function of three spatial coordinates. The number of unknowns in the nonlinear inverse problem reaches 50 million. The developed iterative algorithms for solving the inverse problem are designed for GPU clusters. The main result of this study is testing the developed algorithms on experimental data. The experiments were carried out using a 3D ultrasound tomographic setup developed at Lomonosov Moscow State University. Acoustic properties of the test samples were close to those of human soft tissues. The volume of data collected in experiments is up to 3 GB. Experimental results show the efficiency of the proposed algorithms and confirm that the mathematical model is adequate to reality. The proposed algorithms were tested on the GPU partition of Lomonosov-2 supercomputer.
Section
Section 1. Numerical methods and applications
References
- A. C. Kak and M. Slaney, Principles of Computerized Tomographic Imaging (IEEE Press, New York, 1988).
- M. Sak, N. Duric, P. Littrup, et al., “Using Speed of Sound Imaging to Characterize Breast Density,” Ultrasound Med. Biol. 43 (1), 91-103 (2017).
- A. V. Goncharsky, S. Yu. Romanov, and S. Yu. Seryozhnikov, “Inverse Problems of Layer-by-Layer Ultrasonic Tomography with the Data Measured on a Cylindrical Surface,” Vychisl. Metody Programm. 18, 267-276 (2017).
- A. V. Goncharsky, S. Yu. Romanov and S. Yu. Seryozhnikov, “Low-Frequency Three-Dimensional Ultrasonic Tomography,” Dokl. Akad. Nauk 468 (3), 268-271 (2016) [Dokl. Phys. 61 (5), 211-214 (2016)].
- R. Jiří k, I. Peterlí k, N. Ruiter, et al., “Sound-Speed Image Reconstruction in Sparse-Aperture 3-D Ultrasound Transmission Tomography,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 59 (2), 254-264 (2012).
- J. Wiskin, D. T. Borup, S. A. Johnson, and M. Berggren, “Non-Linear Inverse Scattering: High Resolution Quantitative Breast Tissue Tomography,” J. Acoust. Soc. Am. 131 (5), 3802-3813 (2012).
- V. A. Burov, D. I. Zotov, and O. D. Rumyantseva, “Reconstruction of the Sound Velocity and Absorption Spatial Distributions in Soft Biological Tissue Phantoms from Experimental Ultrasound Tomography Data,” Akust. Zh. 61 (2), 254-273 (2015) [Acoust. Phys. 61 (2), 231-248 (2015)].
- F. Natterer, “Incomplete Data Problems in Wave Equation Imaging,” Inverse Probl. Imag. 4 (4), 685-691 (2010).
- L. Beilina and M. V. Klibanov, Approximate Global Convergence and Adaptivity for Coefficient Inverse Problems (Springer, New York, 2012).
- A. V. Goncharsky, S. Y. Romanov, and S. Y. Seryozhnikov, “A Computer Simulation Study of Soft Tissue Characterization Using Low-Frequency Ultrasonic Tomography,” Ultrasonics 67, 136-150 (2016).
- A. V. Goncharsky and S. Y. Romanov, “A Method of Solving the Coefficient Inverse Problems of Wave Tomography,” Comput. Math. Appl. 77 (4), 967-980 (2019).
- S. Y. Romanov, “Supercomputer Simulation Study of the Convergence of Iterative Methods for Solving Inverse Problems of {3D} Acoustic Tomography with the Data on a Cylindrical Surface,” in Communications in Computer and Information Science (Springer, Cham, 2019), Vol. 965, pp. 388-400.
- A. V. Goncharsky, S. Y. Romanov, and S. Y. Seryozhnikov, “Low-Frequency Ultrasonic Tomography: Mathematical Methods and Experimental Results,” Vestn. Mosk. Univ., Ser. 3: Fiz. Astron., No. 1, 40-47 (2019) [Moscow Univ. Phys. Bull. 74 (1), 43-51 (2019)].
- V. Sadovnichy, A. Tikhonravov, V. Voevodin, and V. Opanasenko, “’Lomonosov’: Supercomputing at Moscow State University,” in Contemporary High Performance Computing: From Petascale toward Exascale (CRC Press, Boca Raton, 2013), pp. 283-308.
- A. V. Goncharsky and S. Y. Romanov, “Inverse Problems of Ultrasound Tomography in Models with Attenuation,” Phys. Med. Biol. 59 (8), 1979-2004 (2014).
- A. V. Goncharsky and S. Y. Romanov, “Iterative Methods for Solving Coefficient Inverse Problems of Wave Tomography in Models with Attenuation,” Inverse Probl. 33 (2) (2017).
doi 10.1088/1361-6420/33/2/025003
- A. Bakushinsky and A. Goncharsky, Ill-Posed Problems: Theory and Applications (Kluwer, Dordrecht, 1994).
- A. N. Tikhonov, A. V. Goncharsky, V. V. Stepanov, and A. G. Yagola, Numerical Methods for the Solution of Ill-Posed Problems (Springer, Dordrecht, 1995; Nauka, Moscow, 1990).
- A. V. Goncharsky and S. Y. Romanov, “Supercomputer Technologies in Inverse Problems of Ultrasound Tomography,” Inverse Probl. 29 (7) (2013).
doi 10.1088/0266-5611/29/7/075004
- B. Engquist and A. Majda, “Absorbing Boundary Conditions for the Numerical Simulation of Waves,” Math. Comp. 31, 629-651 (1977).
- A. Goncharsky and S. Seryozhnikov, “The Architecture of Specialized GPU Clusters Used for Solving the Inverse Problems of 3D Low-Frequency Ultrasonic Tomography,” in Communications in Computer and Information Science (Springer, Cham, 2017), Vol. 793, pp. 363-375.
- S.-Y. Mu and H.-W. Chang, “Dispersion and Local-Error Analysis of Compact LFE-27 Formula for Obtaining Sixth-order Accurate Numerical Solutions of 3D Helmholtz Equation,” Prog. Electromagn. Res. 143, 285-314 (2013).
- S. Romanov, “Optimization of Numerical Algorithms for Solving Inverse Problems of Ultrasonic Tomography on a Supercomputer,” in Communications in Computer and Information Science (Springer, Cham, 2017), Vol. 793, pp. 67-79.
- A. V. Goncharsky, S. Yu. Romanov, and S. Yu. Seryozhnikov, “Low-Frequency 3D Ultrasound Tomography: Dual-Frequency Method,” Vychisl. Metody Programm. 19, 479-495 (2018).
- A. V. Goncharsky, S. Y. Romanov, and S. Y. Seryozhnikov, “Inverse Problems of 3D Ultrasonic Tomography with Complete and Incomplete Range Data,” Wave Motion 51 (3), 389-404 (2014).
- M. Fink, “Time Reversal in Acoustics,” Contemp. Phys. 37 (2), 95-109 (1996).
- A. V. Goncharsky, S. Yu. Romanov, and S. Yu. Seryozhnikov, “The Problem of Choosing Initial Approximations in Inverse Problems of Ultrasound Tomography,” Vychisl. Metody Programm. 18, 312-321 (2017).
- A. Goncharsky and S. Seryozhnikov, “Supercomputer Technology for Ultrasound Tomographic Image Reconstruction: Mathematical Methods and Experimental Results,” in Communications in Computer and Information Science (Springer, Cham, 2019), Vol. 965, pp. 401-413.