OF A ROBUST ALGORITHM FOR IMAGING COMPLEX TISSUE ELASTICITY

Background: Imaging elastic properties of soft tissue is an emerging technology that holds great promise in medical diagnosis [1]. Two steps are usually involved: (1) A dynamic or static displacement field is obtained from any one of various imaging modalities; (2) Desired parameters such as Young's modulus or Poisson's ratio are then estimated by minimizing the discrepancy between the measured data and the outputs of a forward model. This type of inverse problem is likely nonlinear and ill–posed. Iterative gradient descent methods with regularization are often employed to obtain a stable solution [2,3,4].