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Digital image elasto-tomography: mechanical property estimation of silicone phantoms

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Abstract

The application of a surface motion error based elasticity estimation method to hard and soft silicone phantom data is presented. Steady-state harmonic surface motion was measured at a limited number of measurement sites, and fitted with an ideal damped motion path. A finite element (FE) model was used to simulate phantom motion at a range of modulus and damping values. Comparing the simulated cases with the measured motion allowed estimation of the actual elastic properties of the silicone. These estimations compared favorably to static mechanical tests of the material, showing the DIET system can identify homogenous material stiffness values from surface motion measurements alone.

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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. Doyley M, Weaver J, Houten EV, Kennedy F, Paulsen K (2003) Thresholds for detecting and characterizing focal lesions using steady-state MR elastography. Med Phys 30:495–504

    Article  Google Scholar 

  4. Gao L, Parker K, Lerner R, Levinson S (1996) Imaging the elastic properties of tissue—a review. Ultrasound Med Biol 22:959–977

    Article  Google Scholar 

  5. Guo Y, Sivaramakrishna R, Le CC, Suri J, Laxminarayan S (2006) Breast image registration techniques: a survey. Med Biol Eng Comput 44:15–26

    Article  Google Scholar 

  6. 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 

  7. Moore S (2001) Better breast cancer detection. IEEE Spectr 38:50–54

    Article  Google Scholar 

  8. Nandi R, Nandi A, Rangayyan R, Scutt D (2006) Classification of breast masses in mammograms using genetic programming and feature selection. Med Biol Eng Comput 44:683–694

    Article  Google Scholar 

  9. Ophir J, Kallel F, Varghese T, Konofagou E, Alam S, Krouskop T, Garra B, Righetti R (2001) Elastography. Comptes Rendus de l’Academie des Sciences Series IV Physics 2:1193–1212

    Article  Google Scholar 

  10. 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 

  11. 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 Inform Syst Sci 2:512–521

    MATH  Google Scholar 

  12. 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

    Article  Google Scholar 

  13. Samani A, Bishop J, Luginbuhl C, Plewes D (2003) Measuring the elastic modulus of ex vivo small tissue samples. Phys Med Biol 48:2183–2198

    Article  Google Scholar 

  14. 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 

  15. Snoeren P, Karssemeijer N (2004) Thickness correction of mammographic images by means of a global parameter model of the compressed breast. IEEE Trans Med Imaging 23:799–806

    Article  Google Scholar 

  16. Van Houten E, Doyley M, Kennedy F, Paulsen K, Weaver J (2005) A three-parameter mechanical property reconstruction method for MR-based elastic property imaging. IEEE Trans Med Imaging 24:311–234

    Article  Google Scholar 

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Acknowledgements

The authors would like to acknowledge the assistance provided by R. Brown with capturing and processing of the experimental data, and to Dr M. Staiger for his assistance with the static mechanical testing.

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Authors and Affiliations

  1. Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand

    Ashton Peters, J. Geoffrey Chase & Elijah E. W. Van Houten

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  1. Ashton Peters
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  2. J. Geoffrey Chase
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  3. Elijah E. W. Van Houten
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Correspondence to Ashton Peters.

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Peters, A., Chase, J.G. & Van Houten, E.E.W. Digital image elasto-tomography: mechanical property estimation of silicone phantoms. Med Biol Eng Comput 46, 205–212 (2008). https://doi.org/10.1007/s11517-007-0275-x

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  • DOI: https://doi.org/10.1007/s11517-007-0275-x

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