Microwave Contrast Imaging of Breast Tissue From Local Velocity Estimation

Abstract

Abstract-This paper proposes a new method to display microwave images of breast tissue, based on estimation of local microwave velocity from time of flight measurements. Its computational demands are low compared with tomography. It has two major components: 1) the estimation of the travel time of microwaves across the tissue between a set of antennae using a wavelet decomposition, and 2) the estimation of the microwave velocity field from the set of travel times using a low dimensional set of radial basis functions to model local velocity. The technique is evaluated in 2-D on clinical MR-based numerical breast phantoms incorporated in Finite-Difference Time-Domain simulations. The basis functions, used with a regularisation scheme to improve numerical stability, reduce the dimensionality of the inverse problem for computational efficiency and also to improve the robustness to error in velocity estimation. The results support previously published findings that the wavelet transform is suitable for robust measurement of time of flight even in clinically significant simulations, and shows that the velocity contrast images can be constructed so different regions of breast tissue type can be distinguished. In particular, the presence of a tumour is clearly detected, demonstrating the potential of this approach for breast screening.

A Phase Shift and Sum Method for UWB Radar Imaging in Dispersive Media

“…For the specific focal point shown in Fig. 4, there are three valid solutions to (5), and the number of solutions may vary when the focal point switches. Fig.…”

“…Fig. 6 shows the distribution of the number of solutions to (5) for all focal points in ROI. Black, dark gray, light gray, and white denote three, two, one, and zero paths for the wave to propagate from TX to focal point inside ROI, respectively.…”

“…It is interesting to see that the first candidate point (N = 1) shown in Fig. 5, which represents an overall least time, is not a solution to (5), because it is not a "stationary" time length. In addition, despite no solutions to (5) for the white area, a "least time" can still be found among the 135 candidate points by solving (4), which is not a "stationary" solution either, and would be a source of clutters in the image if it was utilized in methods based on TS evaluations.…”

“…U LTRA-WIDEBAND (UWB) radar imaging aims to identify the presence and location of scatters such as underground objects (by ground-penetrating radar) [1], objects behind walls (by through-wall radar) [2], [3], breast tumors [4], [5], and brain stroke regions [6], [7]. A variety of image formation algorithms have been proposed over the last decade.…”

Non‐iterative beamforming based on Huygens principle for multistatic ultrawide band radar: application to breast imaging

“…Microwave tomography techniques attempt to reconstruct dielectric properties by solving non-linear inverse scattering problems, whereas UWB radar techniques solve simpler computational problems by seeking only to identify the significant scatterers inside the target volume. Although tomography offers the highest resolution, its high computational requirements mean that approximations are normally required to reach a throughput appropriate for a clinical environment, resulting in lower resolution (although a high-resolution algorithm may be implemented efficiently using highly parallel computing) [4,5,15]. UWB beamforming techniques are computationally simpler and less dependent on prior model, although may still encounter difficulties in imaging spaces with a complex distribution of dielectric constant.…”