Solutions of Inverse Problems with Potential Application for Breast Tumour Detection Using Microwave Measurements

Abstract

This paper presents one-dimensional and two-dimensional microwave inverse computing methods to detect an internal object using measurements based on a signal applied from the surface of the host material. The modelling of our application system has been aimed towards the in vivo detection of a breast tumour, in particular, and to enable the calculation of the tumour size and its distance from the surface of the breast. However, our approach is also applicable for more general foreign object identification. Complex backscattered electromagnetic waves characterise the relations of the internal properties of the host material. Forward and backscattered signals are used to calculate the impedance and reflection coefficients as a function of the applied microwave frequency. In the study of onedimensional modelling, we discuss the approach to identifying a foreign object hidden inside the host material and we present a method for computing the distance to the object from the surface of the host. Subsequently, a cylindrical coordinate system is used for two-dimensional modelling. A method to compute the size of the object (up to one millimetre in radius) is discussed. Computation of unknown electrical and non-electrical parameters using front-end microwave application is challenging but it is feasible.

Single-Frequency Ultrasound-Based Respiration Rate Estimation with Smartphones

“…Some works use wireless signals to detect the respiration rate. For example, Abdelnasser et al leveraged the WiFi signals [6–10], Lazaro et al used the UWB signals [11, 12], and Rahman et al used a microwave radar to detect respiration [13–15]. These systems require deploying extra wireless transceivers to transmit and receive wireless signals, which makes the system expensive.…”