A fast breast nonlinear elastography reconstruction technique using the Veronda-Westman model
Authors: Mohammadhosein Amooshahi and Abbas Samani.
Abstract:
A common weakness of most conventional imaging modalities is that although they can detect the presence of pathological tissues, they are incapable of classifying tumors and determining whether they are malignant. To address this major issue, elastography has been developed. This is an imaging technique that provides the spatial distribution of tissue stiffness. The main idea behind elastography is the fact that tissue pathological changes such as those associated with cancer trigger significant changes in the tissue mechanical properties. The mechanical behavior of a tissue can be described by parameters characterizing its linear or nonlinear behavior. While soft tissues demonstrate linear behavior under small strains, many clinical applications including elastography involve large strains rendering linear models inaccurate for tissue simulation. Among existing nonlinear models, the Veronda-Westman model has gained much interest because of its exponential form that is consistent with soft tissue mechanical response. However, in elastography where the spatial distribution of this model's parameters must be determined by solving an inverse problem, the exponential form poses serious challenging such as convergence and computation time. To solve the inverse problem, previous methods involved using time-demanding optimization/regularization routines. In this work, we propose a novel technique that does not involve optimization/regularization.