Skip to main content
Log in

Estimating elasticity in heterogeneous phantoms using Digital Image Elasto-Tomography

  • Original Article
  • Published:
Medical & Biological Engineering & Computing Aims and scope Submit manuscript

Abstract

Results from the application of a Digital Image Elasto-Tomography (DIET) system to elasticity distribution estimation in heterogeneous phantoms are presented. Two simple phantoms comprising distinct hard and soft regions were created from silicone, with harmonic surface motion data captured using a steady-state stereo imaging setup. A two-parameter approach to estimating stiffness distribution was used, applying both corroborative and contradictive methods to the inverse problem. The contradictive approach proved more robust in the presence of error in a priori stiffness assumption. These contrast based methods have the ability to reduce the number of parameters required for shape-based stiffness reconstructions, and present a novel approach to inclusion imaging in elastography.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Amestoy P, Guermouche A, L’Excellent JY, Pralet S, Alessandrini G, Morassi A, Rosset E (2006) Hybrid scheduling for the parallel solution of linear systems. Parallel Comput 32:136–156

    Article  MathSciNet  Google Scholar 

  2. Barr R (2006) Clinical applications of a real-time elastography technique in breast imaging. In: Proceedings of the fifth international conference on the ultrasonic measurement and imaging of tissue elasticity, p 51

  3. Gupta S (2006) A new breast cancer test. Time 168(25)

  4. Kinoshita S (2005) Tissue actuation studies for a Digital-Imaged Elasto-Tomography (DIET) breast cancer screening system. PhD Thesis, Department of Mechanical Engineering, University of Canterbury, Canterbury

  5. Krouskop T, Wheeler T, Kallel F, Garra B, Hall T (1998) Elastic moduli of breast and prostate tissues under compression. Ultrason Imaging 20:260–274

    Google Scholar 

  6. Madelin G, Baril N, de Certaines J, Franconi J, Thiaudiere E (2004) NMR characterization of mechanical waves. Annu Rep NMR Spectrosc 53:203–244

    Article  Google Scholar 

  7. Muthupillai R, Rossman PJ, Lomas DJ, Greenleaf JF, Riederer SJ, Ehman RL (1995) Magnetic resonance elastography by direct visualization of propagating acoustic strain waves. Science 269:1854–1857

    Article  Google Scholar 

  8. Ophir J, Céspedes E, Ponnekanti H, Yazdi Y, Li X (1991) Elastography: a quantitative method for imaging the elasticity of biological tissues. Ultrason Imaging 13:111–134

    Article  Google Scholar 

  9. Parker K, Gao L, Lerner R, Levinson S (1996) Techniques for elastic imaging: a review. IEEE Eng Med Biol Mag 15:52–59

    Article  Google Scholar 

  10. Peters A (2007) Digital Image Elasto-Tomography (DIET): mechanical property reconstruction from surface measured displacement data. PhD Thesis, Department of Mechanical Engineering, University of Canterbury, Canterbury

  11. Peters A, Chase J, Houten EV (2008) Digital Image-based Elasto-Tomography: combinatorial and hybrid optimization algorithms for shape-based elastic property reconstruction. IEEE Trans Biomed Eng (in press)

  12. Peters A, Chase J, Houten EV (2008) Digital Image-based Elasto-Tomography: mechanical property estimation of silicone phantoms. Med Biol Eng Comput 46:205–212

    Article  Google Scholar 

  13. Peters A, Milsant A, Rouzé J, Ray L, Chase J, Houten EV (2004) Digital Image-based Elasto-Tomography: proof of concept studies for surface-based mechanical property reconstruction. JSME Int J 47:1117–1123

    Article  Google Scholar 

  14. Peters A, Uwe-Berger H, Chase J, Houten EV (2006) Digital Image-based Elasto-Tomography: non-linear mechanical property reconstruction of homogenous gelatine phantoms. Int J Inf Syst Sci 2:512–521

    MATH  MathSciNet  Google Scholar 

  15. Peters A, Wortmann S, Elliott R, Staiger M, Chase J, Houten EV (2005) Digital Image-based Elasto-Tomography: first experiments in surface based mechanical property estimation of gelatine phantoms. JSME Int J 48:562–569

    Google Scholar 

  16. Richards M, Barbone P, Wu T, Kopans D, Moore R (2003) X-ray tomosynthesis elastography: a feasibility study. In: Proceedings of the second international conference on the ultrasonic measurement and imaging of tissue elasticity, p 90

  17. Rouviŕe O, Yin M, Dresner M, Rossman P, Burgart L, Fidler J, Ehman R (2006) MR elastography of the liver: preliminary results. Radiology 240:440–448

    Article  Google Scholar 

  18. Samani A, Zubovits J, Plewes D (2007) Elastic moduli of normal and pathological human breast tissues: an inversion technique based investigation of 169 samples. Phys Med Biol 52:1565–1576

    Article  Google Scholar 

  19. Sinkus R, Siegmann K, Tanter M, Xydeas T, Fink M (2006) MR elastography is capable of increasing the specificity of MR mammography—influence of rheology on the diagnostic gain. In: Proceedings of the fifth international conference on the ultrasonic measurement and imaging of tissue elasticity, p 111

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to J. Geoffrey Chase.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Peters, A., Chase, J.G. & Van Houten, E.E.W. Estimating elasticity in heterogeneous phantoms using Digital Image Elasto-Tomography. Med Biol Eng Comput 47, 67–76 (2009). https://doi.org/10.1007/s11517-008-0368-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11517-008-0368-1

Keywords

Navigation