High Sound-contrast Inverse Scattering by MR-MF-DBIM Scheme

In ultrasound tomography, cross-sectional images represent the spatial distribution of the physical parameters of a target of interest, which can be obtained based on scattered ultrasound measurements. These measurements can be obtained from dense datasets collected at different transmitter and receiver locations, and using multiple frequencies. The Born approximation method, which provides a simple linear relationship between the objective function and the scattering field, has been adopted to resolve the inverse scattering problem. The distorted Born iterative method (DBIM), which utilizes the first-order Born approximation, is a productive diffraction tomography scheme. In this article, the range of interpolation applications is extended at the multilayer level, taking into account the advantages of integrating this multilayer level with multiple frequencies for the DBIM. Specifically, we consider: (a) a multi-resolution technique, i.e., a multi-step interpolation for the DBIM: MR-DBIM, with the advantage that the normalized absolute error is reduced by 18.67% and 37.21% in comparison with one-step interpolation DBIM and typical DBIM, respectively; (b) the integration of multi-resolution and multi-frequency techniques with the DBIM: MR-MF-DBIM, which is applied to image targets with high sound contrast in a strongly scattering medium. Relative to MR-DBIM, this integration offers a 44.01% reduction in the normalized absolute error

Signal processing based method for solving inverse scattering problems

The problem of reconstructing an image of the permittivity distribution inside a penetrable and strongly scattering object from a finite number of noisy scattered field measurements has always been very challenging because it is ill-posed in nature. Several techniques have been developed which are either computationally very expensive or typically require the object to be weakly scattering. I have developed here a non-linear signal processing method, which will recover images for both strong scatterers and weak scatterers. This nonlinear or cepstral filtering method requires that the scattered field data is first preprocessed to generate a minimum phase function in the object domain. In 2-D or higher dimensional problems, I describe the conditions for minimum phase and demonstrate how an artificial reference wave can be numerically combined with measured complex scattering data in order to enforce this condition, by satisfying Rouche‘s theorem. In the cepstral domain one can filter the frequencies associated with an object from those of the scattered field. After filtering, the next step is to inverse Fourier transform these data and exponentiate to recover the image of the object under test. In addition I also investigate the scattered field sampling requirements for the inverse scattering problem. The proposed inversion technique is applied to the measured experimental data to recover both shape and relative permittivity of unknown objects. The obtained results confirm the effectiveness of this algorithm and show that one can identify optimal parameters for the reference wave and an optimal procedure that results in good reconstructions of a penetrable, strongly scattering permittivity distribution

Microwave Sensing and Imaging

In recent years, microwave sensing and imaging have acquired an ever-growing importance in several applicative fields, such as non-destructive evaluations in industry and civil engineering, subsurface prospection, security, and biomedical imaging. Indeed, microwave techniques allow, in principle, for information to be obtained directly regarding the physical parameters of the inspected targets (dielectric properties, shape, etc.) by using safe electromagnetic radiations and cost-effective systems. Consequently, a great deal of research activity has recently been devoted to the development of efficient/reliable measurement systems, which are effective data processing algorithms that can be used to solve the underlying electromagnetic inverse scattering problem, and efficient forward solvers to model electromagnetic interactions. Within this framework, this Special Issue aims to provide some insights into recent microwave sensing and imaging systems and techniques

The Use of GPR and Microwave Tomography for the Assessment of the Internal Structure of Hollow Trees

Peer reviewedPostprin

Recent Advances in Microwave Imaging for Breast Cancer Detection

Breast cancer is a disease that occurs most often in female cancer patients. Early detection can significantly reduce the mortality rate. Microwave breast imaging, which is noninvasive and harmless to human, offers a promising alternative method to mammography. This paper presents a review of recent advances in microwave imaging for breast cancer detection. We conclude by introducing new research on a microwave imaging system with time-domain measurement that achieves short measurement time and low system cost. In the time-domain measurement system, scan time would take less than 1 sec, and it does not require very expensive equipment such as VNA