Dynamic Ultrasound Scatterer Simulation Model Using Field-II and FEM for Speckle Tracking
There is a growing interest in the use of ultrasonic speckle tracking for biomedical image formation of tissue deformation. Speckle tracking is angle independent and has an ability to differentiate soft tissue into benign and malignant regions. In this paper a simulation model for dynamic ultrasound scatterer is presented. The model composes Field-II ultrasonic scatterers and FEM (ANSYS-11) nodes as a regional tissue deformation. A performance evaluation is presented on axial displacement and strain fields estimation of a uniformly elastic model, using speckle tracking based 1D cross-correlation of optimally segmented pre and post-deformation frames. Optimum correlation window length is investigated in terms of highest signal-to-noise ratio (SNR) for a selected region of interest of a smoothed displacement field. Finally, gradient based strain field of both smoothed and non-smoothed displacement fields are compared. Simulation results from the model are shown to compare favorably with FEM results.
[1] http://field-ii.dk/?background.html.
[2] Jensen, J.A. and N.B. Svendsen, Calculation of pressure fields from
arbitrarily shaped, apodized, and excited ultrasound transducers.
Ultrasonics, Ferroelectrics and Frequency Control, IEEE Transactions
on, 1992. 39(2): p. 262-267.
[3] Meunier, J. and M. Bertrand, Ultrasonic texture motion analysis: theory
and simulation. Medical Imaging, IEEE Transactions on, 1995. 14(2): p.
293-300.
[4] Thijssen, J.M. and B.J. Oosterveld. Speckle and Texture in Echography:
Artifact or Information? in IEEE 1986 Ultrasonics Symposium. 1986.
[5] Wagner, R.F., M.F. Insana, and S.W. Smith, Fundamental correlation
lengths of coherent speckle in medical ultrasonic images. Ultrasonics,
Ferroelectrics and Frequency Control, IEEE Transactions on, 1988.
35(1): p. 34-44.
[6] Jensen, J.A. Simulation of advanced ultrasound systems using Field II.
in Biomedical Imaging: Nano to Macro, 2004. IEEE International
Symposium on. 2004.
[7] Marion, A. and D. Vray, Toward a real-time simulation of ultrasound
image sequences based on a 3-D set of moving scatterers. Ultrasonics,
Ferroelectrics and Frequency Control, IEEE Transactions on, 2009.
56(10): p. 2167-2179.
[8] Madenci, E. and I. Guven, The Finite Element Method And
Applications In Engineering Using ANSYS. Springer, 2006.
[9] Palmeri, M.L., et al., A finite-element method model of soft tissue
response to impulsive acoustic radiation force. Ultrasonics,
Ferroelectrics and Frequency Control, IEEE Transactions on, 2005.
52(10): p. 1699-1712.
[10] Lopata, R.G.P., et al., Performance Evaluation of Methods for Two-
Dimensional Displacement and Strain Estimation Using Ultrasound
Radio Frequency Data. Ultrasound in Medicine & Biology, 2009. 35(5):
p. 796-812.
[11] Lopata, R.G.P., 2D and 3D Ultrasound Strain Imaging: Methods and in
vivo Applications. PhD Thesis, Radboud University Nijmegen, 2010.
[12] Varghese, T., M. Bilgen, and J. Ophir, Multiresolution imaging in
elastography. Ultrasonics, Ferroelectrics and Frequency Control, IEEE
Transactions on, 1998. 45(1): p. 65-75.
[13] Kallel, F. and J. Ophir, A least-squares strain estimator for elastography.
Ultrason Imaging, 1997. 19: p. 195–208.
[14] Bilgen, M. and M.F. Insana, Error analysis in acoustic elastography. I.
Displacement estimation estimation. Acoustical Society of America,
1997. 101(2).
[15] Ophir, J., et al., Elastography: Ultrasonic estimation and imaging of the
elastic properties of tissues. Proceedings of the Institution of Mechanical
Engineers, Part H: Journal of Engineering in Medicine, 1999. 213(3): p.
203-233.
[16] Walker, W.F. and G.E. Trahey, A fundamental limit on delay estimation
using partially correlated speckle signals. Ultrasonics, Ferroelectrics and
Frequency Control, IEEE Transactions on, 1995. 42(2): p. 301-308.
[17] Jensen, J.a., Field: a Program For simulating Ultrasound systems. Med.
Biol. Eng. Comput, 1996. 34(1 , Part 1): p. 1351-1353.
[18] Hoff, L., Acoustic Characterization of Contrast Agents for Medical
Ultrasound Imaging. Kluwer Academic Publishers, 2001.
[19] Wagner, R.F., et al., Statistics of Speckle in Ultrasound B-Scans. Sonics
and Ultrasonics, IEEE Transactions on, 1983. 30(3): p. 156-163.
[20] Bilgen, M. and M.F. Insana, Error analysis in acoustic elastography. II.
Strain estimation and SNR analysis. Acoustical Society of America,
1997. 101(2): p. 1147-1154.
[1] http://field-ii.dk/?background.html.
[2] Jensen, J.A. and N.B. Svendsen, Calculation of pressure fields from
arbitrarily shaped, apodized, and excited ultrasound transducers.
Ultrasonics, Ferroelectrics and Frequency Control, IEEE Transactions
on, 1992. 39(2): p. 262-267.
[3] Meunier, J. and M. Bertrand, Ultrasonic texture motion analysis: theory
and simulation. Medical Imaging, IEEE Transactions on, 1995. 14(2): p.
293-300.
[4] Thijssen, J.M. and B.J. Oosterveld. Speckle and Texture in Echography:
Artifact or Information? in IEEE 1986 Ultrasonics Symposium. 1986.
[5] Wagner, R.F., M.F. Insana, and S.W. Smith, Fundamental correlation
lengths of coherent speckle in medical ultrasonic images. Ultrasonics,
Ferroelectrics and Frequency Control, IEEE Transactions on, 1988.
35(1): p. 34-44.
[6] Jensen, J.A. Simulation of advanced ultrasound systems using Field II.
in Biomedical Imaging: Nano to Macro, 2004. IEEE International
Symposium on. 2004.
[7] Marion, A. and D. Vray, Toward a real-time simulation of ultrasound
image sequences based on a 3-D set of moving scatterers. Ultrasonics,
Ferroelectrics and Frequency Control, IEEE Transactions on, 2009.
56(10): p. 2167-2179.
[8] Madenci, E. and I. Guven, The Finite Element Method And
Applications In Engineering Using ANSYS. Springer, 2006.
[9] Palmeri, M.L., et al., A finite-element method model of soft tissue
response to impulsive acoustic radiation force. Ultrasonics,
Ferroelectrics and Frequency Control, IEEE Transactions on, 2005.
52(10): p. 1699-1712.
[10] Lopata, R.G.P., et al., Performance Evaluation of Methods for Two-
Dimensional Displacement and Strain Estimation Using Ultrasound
Radio Frequency Data. Ultrasound in Medicine & Biology, 2009. 35(5):
p. 796-812.
[11] Lopata, R.G.P., 2D and 3D Ultrasound Strain Imaging: Methods and in
vivo Applications. PhD Thesis, Radboud University Nijmegen, 2010.
[12] Varghese, T., M. Bilgen, and J. Ophir, Multiresolution imaging in
elastography. Ultrasonics, Ferroelectrics and Frequency Control, IEEE
Transactions on, 1998. 45(1): p. 65-75.
[13] Kallel, F. and J. Ophir, A least-squares strain estimator for elastography.
Ultrason Imaging, 1997. 19: p. 195–208.
[14] Bilgen, M. and M.F. Insana, Error analysis in acoustic elastography. I.
Displacement estimation estimation. Acoustical Society of America,
1997. 101(2).
[15] Ophir, J., et al., Elastography: Ultrasonic estimation and imaging of the
elastic properties of tissues. Proceedings of the Institution of Mechanical
Engineers, Part H: Journal of Engineering in Medicine, 1999. 213(3): p.
203-233.
[16] Walker, W.F. and G.E. Trahey, A fundamental limit on delay estimation
using partially correlated speckle signals. Ultrasonics, Ferroelectrics and
Frequency Control, IEEE Transactions on, 1995. 42(2): p. 301-308.
[17] Jensen, J.a., Field: a Program For simulating Ultrasound systems. Med.
Biol. Eng. Comput, 1996. 34(1 , Part 1): p. 1351-1353.
[18] Hoff, L., Acoustic Characterization of Contrast Agents for Medical
Ultrasound Imaging. Kluwer Academic Publishers, 2001.
[19] Wagner, R.F., et al., Statistics of Speckle in Ultrasound B-Scans. Sonics
and Ultrasonics, IEEE Transactions on, 1983. 30(3): p. 156-163.
[20] Bilgen, M. and M.F. Insana, Error analysis in acoustic elastography. II.
Strain estimation and SNR analysis. Acoustical Society of America,
1997. 101(2): p. 1147-1154.
@article{"International Journal of Medical, Medicine and Health Sciences:65166", author = "Aws Al-azawi and John Soraghan", title = "Dynamic Ultrasound Scatterer Simulation Model Using Field-II and FEM for Speckle Tracking", abstract = "There is a growing interest in the use of ultrasonic speckle tracking for biomedical image formation of tissue deformation. Speckle tracking is angle independent and has an ability to differentiate soft tissue into benign and malignant regions. In this paper a simulation model for dynamic ultrasound scatterer is presented. The model composes Field-II ultrasonic scatterers and FEM (ANSYS-11) nodes as a regional tissue deformation. A performance evaluation is presented on axial displacement and strain fields estimation of a uniformly elastic model, using speckle tracking based 1D cross-correlation of optimally segmented pre and post-deformation frames. Optimum correlation window length is investigated in terms of highest signal-to-noise ratio (SNR) for a selected region of interest of a smoothed displacement field. Finally, gradient based strain field of both smoothed and non-smoothed displacement fields are compared. Simulation results from the model are shown to compare favorably with FEM results.
", keywords = "Speckle tracking, tissue deformation, ultrasonic simulation.", volume = "7", number = "9", pages = "589-5", }
