Superlens Enhanced 2-D Microwave Tomography With Contrast Source Inversion Method

Anton Menshov,Vladimir I Okhmatovski

doi:10.1109/ojap.2021.3066304

Abstract

The contrast source inversion (CSI) algorithm is one of the primary techniques used for solution of non-linear inverse problems in microwave tomography. In this paper, we describe a modification of the CSI method adapted to imaging of the 2-D objects in the presence of the focusing media under TM-polarization. The focusing media is presented in the form of the Veselago lens. The data domain and imaging domain are properly positioned with respect to the location of the lens. Specifically, the sensors are located at the focal points of the lens with respect to the location of the individual pixels discretizing the contrast source. Such positioning of the source and observation locations in the presence of the lens, eliminates rank deficiency in the formulation of the inverse problem and results in significant improvements to both convergence speed of underlying conjugate gradient iterations and the accuracy of the image reconstruction in the CSI method.

Highlights

M ICROWAVE Tomography (MWT) has various important applications in medical imaging [1], nondestructive testing [2], security screening [3], structural health monitoring [4], remote sensing [5], and other areas [6]
The paper describes a modification of the Contrast Source Inversion (CSI) algorithm which conducts image reconstruction of an object from its scattered electromagnetic field in the presence of a focusing media
The focusing media is formed by the Veselago lens which is properly positioned with respect to the object and the sensor locations at which the scattered field data is collected

Summary

Introduction

M ICROWAVE Tomography (MWT) has various important applications in medical imaging [1], nondestructive testing [2], security screening [3], structural health monitoring [4], remote sensing [5], and other areas [6]. While qualitative imaging techniques [7], such as Ground Penetrating Radar [8] and Synthetic Aperture Radar [9] methods, have been well developed and can often provide useful information about the location and shape of the imaged objects, it is the more accurate quantitative methods which have a potential to greatly expand the areas of MWT applicability. The two primary methods of quantitative MWT are the CSI method [10] and the Distorted Born Iterative Method (DBIM) [11] (a.k.a. Gauss-Newton Inversion (GNI) method [19]). Gauss-Newton Inversion (GNI) method [19]) Both methods are iterative in nature and provide about equal abilities in quality of reconstruction and the overall computational cost [12], [13]

Methods

Results

Conclusion