LI Ruijing, CHEN Houjin, PENG Yahui, et al., “Comparison of Four Forward Models for Breast Imaging in Ultrasound Computed Tomography,” Chinese Journal of Electronics, vol. 28, no. 4, pp. 805-816, 2019, doi: 10.1049/cje.2019.05.008
Citation: LI Ruijing, CHEN Houjin, PENG Yahui, et al., “Comparison of Four Forward Models for Breast Imaging in Ultrasound Computed Tomography,” Chinese Journal of Electronics, vol. 28, no. 4, pp. 805-816, 2019, doi: 10.1049/cje.2019.05.008

Comparison of Four Forward Models for Breast Imaging in Ultrasound Computed Tomography

doi: 10.1049/cje.2019.05.008
Funds:  This work is supported by the National Natural Science Foundation of China (No.61571036).
  • Received Date: 2018-11-20
  • Rev Recd Date: 2019-04-13
  • Publish Date: 2019-07-10
  • Ultrasound computed tomography (USCT) is considered to have great potential for breast cancer screening. Compared with ray-based methods, Waveform inversion (WI) methods obtain high spatial resolution images because they consider higher-order diffraction effects. For the WI method, considering more properties of the medium in a forward model can estimate more accurate images. However, longer reconstruction time is required. Therefore, to reduce the reconstruction time, three hypotheses are set in this work to develop the medium under different conditions. We compare the reconstructed images using the four forward models to analyze the effects of the various considered medium properties, which include the sound speed, density of the medium, acoustic absorption and dispersion. To reduce the difficulty of hardware manufacturing, a square border ultrasonic transducer array is adopted in the USCT data acquisition system. Penalized leastsquares optimization problems are constructed to obtain numerical solutions of the sound speed and bulk modulus distributions. The reconstruction of the bulk modulus makes the reconstructed sound speed images more accurate. Computer simulations are conducted to compare reconstructed images using the four forward models under different noise conditions. A numerical breast phantom is used to evaluate the performance. The results suggest that for breast imaging, the forward model (which only considers the heterogeneous sound speed) is a compromise option between image accuracy and computational time.
  • loading
  • N. Duric, P. Littrup, L. Poulo, et al., “Detection of breast cancer with ultrasound tomography: First results with the computed ultrasound risk evaluation (CURE) prototype”, Medical Physics, Vol.34, No.2, pp.773–785, 2007.
    N. Duric, P. Littrup, O. Roy, et al., “Breast imaging with ultrasound tomography: Initial results with SoftVue”, IEEE Int. Ultrasonics Symp., pp.382–385, 2013.
    K. J. Opieliński, P.Pruchnicki, T.Gudra, et al., “Imaging results of multi-modal ultrasound computerized tomography system designed for breast diagnosis”, Computerized Medical Imaging and Graphics, Vol.46, No.2, pp.83–94, 2015.
    X. Liu, Y. An, B. Yu, et al., “Analysis of commonly and specifically dysregulated pathways in three women cancers”, Chinese Journal of Electronics, Vol.27, No.5, pp.1043–1049, 2018.
    C. Zheng, H. Peng and W. Zhao, “Ultrasound imaging based on coherent plane wave compounding weighted by sign coherence factor”, Acta Electronica Sinica, Vol.46, No.1, pp.31–38, 2018. (in Chinese)
    X. Li, X. Li and R. WANG, “Compressed sensing based ultrasonic nondestructive testing by the use of sparse deconvolution”, Chinese Journal of Electronics, Vol.22, No.2, pp.405–409, 2013.
    K. Wu, Y. Zhang, Z. Zhao, et al., “Characterization for ultrasonic harmonic of tissue based on nakagami distribution”, Acta Electronica Sinica, Vol.46, No.7, pp.1639–1643, 2018. (in Chinese)
    G. Yin, H. Fan, D. Kang, et al., “The optimization research on element failure of ultrasonic array transducer”, Acta Electronica Sinica, Vol.45, No.8, pp.1995–2000, 2017. (in Chinese)
    B. Arnal, G. F. Pinton, P. Garapon, et al., “Global approach for transient shear wave inversion based on the adjoint method: A comprehensive 2D simulation study”, Physics in Medicine and Biology, Vol.58, No.19, pp.6765–6778, 2013.
    K. Wang, T. Matthews, F. Anis, et al., “Waveform inversion with source encoding for breast sound speed reconstruction in ultrasound computed tomography”, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol.62, No.3, pp.475–493, 2015.
    T. Matthews, K. Wang, C. Li, et al., “Regularized dual averaging image reconstruction for full-wave ultrasound computed tomography”, IEEE Transactions on Ultrasonics Ferroelectrics & Frequency Control, Vol.64, No.5, pp.811–825, 2017.
    Guoyao Wu, “Research on ultrasound tomography reconstruction approach”, Ph.D. Thesis, Harbin Institute of Technology, 2011.
    M. Birk, E. Kretzek, P. Figuli, et al., “High-speed medical imaging in 3D ultrasound computer tomography”. IEEE Transactions on Parallel and Distributed Systems, Vol.27, No.2, pp.455–467, 2016.
    N. Q. Nguyen and L. Huang, “Ultrasound bent-ray tomography using both transmission and reflection data”, Proc. SPIE, Vol. 9040, doi:10.1117/12.2043275, 2014.
    L. Huang, Y. Lin, Z. Zhang, et al., “Breast ultrasound waveform tomography: Using both transmission and reflection data, and numerical virtual point sources”, Proc. SPIE, Vol.9040, doi:10.1117/12.2043136, 2014.
    C. Li, N. Duric, P. Littrup, et al., “In vivo breast soundspeedimaging with ultrasound tomography”, Ultrasound Med. Biol., Vol.35, No.10, pp.1615–1628, 2009.
    G. Glover, “Characterization of in vivo breast tissue by ultrasonic time-of-flight computed tomography”, in National Bureau of Standards Int. Symp. Ultrasonic Tissue Characterization, National Scienc Foundation, Ultrasonic Tissue Characterization Ⅱ, pp.221–225, 1979.
    M. Pérezliva, J. L.Herraiz, J. M. Udías, et al., “Time domain reconstruction of sound speed and attenuation in ultrasound computed tomography using full wave inversion”, J. Acoust. Soc. Am., Vol.141, No.3, pp.1595–1604, 2017.
    S. Bernard, V. Monteiller, D. Komatitsch, et al., “Ultrasonic computed tomography based on full-waveform inversion for bone quantitative imaging”, Physics in Medicine and Biology, Vol.62, pp.7011–7035, 2017.
    A. Tarantola, “A strategy for nonlinear inversion of seismic reflection data”, Geophysics, Vol.51, No.10, pp.1893–1903, 1986.
    C. Sheng-Chang and C. Guo-Xin, “Full waveform inversion of the second-order time integral wavefield”, Chinese Journal of Geophysics, Vol.59, No.6, pp.676–690, 2016.
    S. C. Chen andG. X. Chen, “Time-damping full waveform inversion of multi-dominant-frequency wave fields”, Chinese Journal of Geophysics, Vol.60, No.6, pp.678–688, 2017.
    Y. Li, Y. Choi, T. Alkhalifah, et al., “Full-waveform inversion using a nonlinearly smoothed wave field”, Geophysics, Vol. 83, No. 2, pp. R117–R127, 2018.
    X. Guo, H. Liu, Y. Shi, et al., “Dynamic convolution-based misfit function for time domain full waveform inversion”, Pure & Applied Geophysics, doi:10.1007/s00024-018-1968-9, 2018.
    Y. Liu, B. He, H. Lu, et al., “Full intensity waveform inversion”, Geophysics, Vol.83, No.6, PP.R649–R658, 2018.
    B. E. Treeby, J. Jaros, A. P. Rendell, et al., “Modeling nonlinear ultrasound propagation in heterogeneous media with power law absorption using a k-space pseudo spectral method”, J. Acoust. Soc. Am., Vol.131, No.6, pp.4324–4336, 2012.
    B. E. Treeby and B. Cox, “Modeling power law absorption anddispersion for acoustic propagation using the fractional Laplacian”, J. Acoust. Soc. Am., Vol.127, No.5, pp.2741–2748, 2010.
    B. Qin and G. Lambare, “Joint inversion of velocity and density in preserved-amplitude full-waveform inversion”, SEG International Exposition and 87th Annual Meeting, pp.1325–1330, 2016.
    F. A. Duck,“Chapter 4- Acoustic properties of tissue at ultrasonic frequencies”, in Physical Properties of Tissue, Elsevier Ltd., pp.73–135, 1990.
    D. Zhao, H. Q. Du and W. B. Mei, “Hybrid Weighted l1-Total variation constrained reconstruction for MR image”, Chinese Journal of Electronics, Vol.23, No.4, pp.747–752, 2014.
    Q. S. Lian, T. J. Wei, S. Z. Chen et al., “A phase retrieval algorithm based on total variation regularization”, Acta Electronica Sinica, Vol.45, No.1, pp.54–60, 2017.
    S. J. Norton, “Iterative inverse scattering algorithms: Methods of computing Frechet derivatives”, J. Acoust. Soc. Am., Vol.106, No.5, pp.2653–2660, 1999.
    R.E. Plessix, “A review of the adjoint-state method for computing the gradient of a functional with geophysical applications”, Geophys. J. Int., Vol.167, No.2, pp.495–503, 2006.
    Z. Zhang, L. Huang and Y. Lin, “Efficient implementation of ultrasound waveform tomography using source encoding”, in SPIE Medical Imaging. International Society for Optics and Photonics, Article No.832003, 2012.
    E. Haber, M. Chung and F. Herrmann, “An effective method for parameter estimation with PDE constraints with multiple right hand sides”, SIAM J. Optimiz., Vol.22, No.3, pp.739–757, 2012.
    C. Glide, N. Duric and P. Littrup, “Novel approach to evaluating breast density utilizing ultrasound tomography”, Medical Physics, Vol.34, No.2, pp.744–753, 2007.
    H. Zhang, Theoretical Acoustics (2nd Edition), Higher Education Press (Beijing), pp.186–210, 2012.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (523) PDF downloads(183) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return