On the detection of medium inhomogeneity by contrast agent: wave scattering models and numerical implementations

TL;DR

This paper develops a numerical method to detect and reconstruct medium inhomogeneity by analyzing wave scattering patterns caused by a small droplet, enabling improved imaging in inhomogeneous media.

Contribution

It introduces an efficient approximate scheme for computing scattered waves and a reconstruction algorithm based on far-field patterns and the dual reciprocity method.

Findings

The scheme accurately computes scattered waves in inhomogeneous media.

The reconstruction method effectively recovers the bulk modulus inside a domain.

Numerical results validate the proposed inversion approach.

Abstract

We consider the wave scattering and inverse scattering in an inhomogeneous medium embedded a homogeneous droplet with a small size, which is modeled by a constant mass density and a small bulk modulus. Based on the Lippmann-Schwinger integral equation for scattering wave in inhomogeneous medium, we firstly develop an efficient approximate scheme for computing the scattered wave as well as its far-field pattern for any droplet located in the inhomogeneous background medium. By establishing the approximate relation between the far-field patterns of the scattered wave before and after the injection of a droplet, the scattered wave of the inhomogeneous medium after injecting the droplet is represented by a measurable far-field patterns, and consequently the inhomogeneity of the medium can be reconstructed from the Helmholtz equation. Finally, the reconstruction process in terms of the dual reciprocity method is proposed to realize the numerical algorithm for recovering the bulk modulus function inside a bounded domain in three dimensional space, by moving the droplet inside the bounded domain. Numerical implementations are given using the simulation data of the far-field pattern to show the validity of the reconstruction scheme, based on the mollification scheme for dealing with the ill-posedness of this inverse problem.