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An inverse problem approach for elasticity imaging through vibroacoustics.

Publication ,  Journal Article
Aguiló, MA; Aquino, W; Brigham, JC; Fatemi, M
Published in: IEEE transactions on medical imaging
April 2010

A methodology for estimating the spatial distribution of elastic moduli using the steady-state dynamic response of solids immersed in fluids is presented. The technique relies on the ensuing acoustic field from a remotely excited solid to inversely estimate the spatial distribution of Young's modulus of biological structures (e.g., breast tissue). This work proposes the use of Gaussian radial basis functions (GRBF) to represent the spatial variation of elastic moduli. GRBF are shown to possess the advantage of representing smooth functions with quasi-compact support and can efficiently represent elastic moduli distributions such as those that occur in soft biological tissue in the presence of unhealthy tissue (e.g., tumors and calcifications). The direct problem consists of a coupled acoustic-structure interaction boundary-value problem solved in the frequency domain using the finite element method. The inverse problem is cast as an optimization problem in which the error functional is defined as a measure of discrepancy between an experimentally measured response and a finite element representation of the system. Nongradient based optimization algorithms are used to solve the resulting optimization problem. The feasibility of the proposed approach is demonstrated through a series of simulations and an experiment. For comparison purposes, the surface velocity response was also used for the inverse characterization as the measured response in place of the acoustic pressure.

Duke Scholars

Published In

IEEE transactions on medical imaging

DOI

EISSN

1558-254X

ISSN

0278-0062

Publication Date

April 2010

Volume

29

Issue

4

Start / End Page

1012 / 1021

Related Subject Headings

  • Vibration
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Nuclear Medicine & Medical Imaging
  • Normal Distribution
  • Models, Statistical
  • Models, Biological
  • Image Interpretation, Computer-Assisted
  • Image Enhancement
  • Humans
 

Citation

APA
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ICMJE
MLA
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Aguiló, M. A., Aquino, W., Brigham, J. C., & Fatemi, M. (2010). An inverse problem approach for elasticity imaging through vibroacoustics. IEEE Transactions on Medical Imaging, 29(4), 1012–1021. https://doi.org/10.1109/tmi.2009.2039225
Aguiló, Miguel A., Wilkins Aquino, John C. Brigham, and Mostafa Fatemi. “An inverse problem approach for elasticity imaging through vibroacoustics.IEEE Transactions on Medical Imaging 29, no. 4 (April 2010): 1012–21. https://doi.org/10.1109/tmi.2009.2039225.
Aguiló MA, Aquino W, Brigham JC, Fatemi M. An inverse problem approach for elasticity imaging through vibroacoustics. IEEE transactions on medical imaging. 2010 Apr;29(4):1012–21.
Aguiló, Miguel A., et al. “An inverse problem approach for elasticity imaging through vibroacoustics.IEEE Transactions on Medical Imaging, vol. 29, no. 4, Apr. 2010, pp. 1012–21. Epmc, doi:10.1109/tmi.2009.2039225.
Aguiló MA, Aquino W, Brigham JC, Fatemi M. An inverse problem approach for elasticity imaging through vibroacoustics. IEEE transactions on medical imaging. 2010 Apr;29(4):1012–1021.

Published In

IEEE transactions on medical imaging

DOI

EISSN

1558-254X

ISSN

0278-0062

Publication Date

April 2010

Volume

29

Issue

4

Start / End Page

1012 / 1021

Related Subject Headings

  • Vibration
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Nuclear Medicine & Medical Imaging
  • Normal Distribution
  • Models, Statistical
  • Models, Biological
  • Image Interpretation, Computer-Assisted
  • Image Enhancement
  • Humans