Supercomputer Simulations in Design of Ultrasound Tomography Devices

Alexander V. Goncharsky; Sergey Y. Seryozhnikov

doi:10.14529/jsfi180321

Authors

Alexander V. Goncharsky Lomonosov Moscow State University
Sergey Y. Seryozhnikov

DOI:

https://doi.org/10.14529/jsfi180321

Abstract

The paper considers the use of supercomputers in design of medical ultrasound tomography devices. The mathematical models describing the wave propagation in ultrasound tomography should take into account such physical phenomena as diffraction, multiple scattering, and so on. The inverse problem of wave tomography is posed as a coefficient inverse problem with respect to the wave propagation velocity and the absorption factor. Numerous simulations made it possible to determine the optimal parameters of an ultrasound tomograph in order to obtain a spatial resolution of 1.5 mm suitable for early-stage breast cancer diagnosis. The developed methods were tested both on model problems and on real data obtained at the experimental test bench for tomographic studies. The computations were performed on GPU devices of Lomonosov-2 supercomputer at Lomonosov Moscow State University.

References

Birk, M., Dapp, R., Ruiter, N.V., Becker, J.: GPU-based iterative transmission reconstruction in 3D ultrasound computer tomography. J. Parallel Distrib. Comput. 74, 1730–1743 (2014), DOI: 10.1016/j.jpdc.2013.09.007

Goncharsky, A.V., Seryozhnikov, S.Y.: The Architecture of Specialized GPU Clusters Used for Solving the Inverse Problems of 3D Low-Frequency Ultrasonic Tomography. In: Voevodin, V., Sobolev, S. (eds.) Supercomputing. RuSCDays 2017. Communications in Computer and Information Science. vol. 793, pp. 363–395. Springer (2017), DOI: 10.1007/978-3-319-71255-0 29

Goncharsky, A.V., Romanov, S.Y.: Inverse problems of ultrasound tomography in models with attenuation. Phys. Med. Biol. 59(8), 1979–2004 (2014), DOI: 10.1088/0031-9155/59/8/1979

Goncharsky, A.V., Romanov, S.Y.: Iterative methods for solving coefficient inverse problems of wave tomography in models with attenuation. Inverse Probl. 33(2), 025003 (2017), DOI: 10.1088/1361-6420/33/2/025003

Goncharsky, A., Romanov, S., Seryozhnikov, S.: A computer simulation study of soft tissue characterization using low-frequency ultrasonic tomography. Ultrasonics 67, 136–150 (2016), DOI: 10.1016/j.ultras.2016.01.008

Romanov, S.: Optimization of Numerical Algorithms for Solving Inverse Problems of Ultrasonic Tomography on a Supercomputer. In: Voevodin, V., Sobolev, S. (eds.) Supercomputing. RuSCDays 2017. Communications in Computer and Information Science. vol. 793, pp. 67–79. Springer (2017), DOI: 10.1007/978-3-319-71255-0_6

Sadovnichy, V., Tikhonravov, A., Voevodin, Vl., Opanasenko, V.: “Lomonosov”: Supercomputing at Moscow State University. In: Contemporary High Performance Computing: From Petascale toward Exascale. pp. 287–307. CRC Press, Boca Raton, USA (2013)

Tikhonov, A.N.: Solution of incorrectly formulated problems and the regularization method. Soviet Math. Dokl. 4, 1035–1038 (1963)

Tikhonov, A.N., Goncharsky, A.V., Stepanov, V.V., Yagola, A.G.: Numerical Methods for the Solution of Ill-Posed Problems. Springer Netherlands (1995), DOI: 10.1007/978-94-015-8480-7

Wiskin, J., Borup, D., Andre, M., Johnson, S., Greenleaf, J., Parisky, Y., Klock, J.: Threedimensional nonlinear inverse scattering: quantitative transmission algorithms, refraction corrected reflection, scanner design, and clinical results. J. Acoust. Soc. Am. 133(5), 3229–3229 (2013), DOI: 10.1121/1.4805138