Detection of Lesions in Soft Tissues Based on Nonlinear Constitutive Model

With the purpose of accurate detection and classification of various pathologies in soft tissues in a noninvasive way, a variety of elastography techniques has been introduced in the last two decades. The linear and nonlinear constitutive models of soft tissues have been exploited in several elastography techniques. In this paper, we discuss a technique for estimating the mechanical properties of soft tissue, which uses the nonlinear hyperelastic constitutive model as the basis. The limitations of detecting tumors on the basis of the linear constitutive model, that some of them have been mentioned in this paper, impel us to employ the hyperelastic model as a more realistic strategy for detecting lesions in the soft tissue. The estimated hyperelastic parameters of the polynomial model for a simulated phantom are presented in this paper, which have been obtained by utilizing appropriate regularization methods and considering proper regularization parameter, initial condition and hypothetical hyperelastic parameters. The hyperelastic parameters have been estimated after simulating the response of the phantom to the compression and computing some mechanical variables such as the displacement for the phantom. The propounded explanations and results indicate that the determination of hyperelastic parameters of soft tissues could culminate in the superior detection of their lesions.