Biomechanical imaging (BMI) is a method used to noninvasively quantify the mechanical properties of tissue. These mechanical properties can be displayed as images and used to visualize the interior of tissue and potentially help diagnose various diseases [1]. The first step in the BMI method is to load and measure the resulting deformation (displacements or velocities) of soft tissue. The measured deformation along with the conservation of momentum equations is then used in an inverse problem formulation to infer the mechanical properties. In this talk, I describe two inverse problem formulations for reconstructing the mechanical properties. I also describe a numerical method used to solve the inverse problems.

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References
[1] Paul E. Barbone and Assad A. Oberai. A review of the mathematical and computational foundations of biomechanical imaging. In D. Suvranu, G. Farshid, and M. Mohammad, editors, Computational Modeling in Biomechanics, pages 375–408. Springer, 2010.