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Nonlinear elasticity imaging

Authors: Sevan Goenezen; Assad A. Oberai; Jean-Francois Dord; Zac Sink; Paul Barbone;

Nonlinear elasticity imaging

Abstract

We present the solution of the nonlinear inverse elasticity problem, wherein we image the linear and nonlinear hyperelastic properties of soft tissues in-vivo. For this, we solve a constrained optimization problem iteratively. The discrepancy between measured and predicted displacement fields is minimized in the objective function in the presence of regularization. The predicted displacement fields satisfy the equilibrium equations of elasticity from the current estimate of the elastic properties. The measured displacement fields are determined from a sequence of ultrasound radio frequency data while the tissue is slowly compressed. We model the tissue to have an exponential stress-stretch relation and capture its nonlinear response with a nonlinear parameter at large deformations.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Average
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