Model-based imaging techniques utilizing microwave signal illumination rely heavily on the ability to accurately represent the wave propagation with a suitable numerical model. To date, the highest quality images from our prototype system have been achieved utilizing a single transmitter/single receiver measurement system where both antennas are manually repositioned to facilitate multiple illuminations of the imaging region, thus requiring long data acquisition times. In an effort to develop a system that can acquire data in a real time manner, a 32-channel network has been fabricated with all ports capable of being electronically selected for either transmit or receive mode. The presence of a complete array of antenna elements at data collection time perturbs the field distributions being measured, which can subsequently degrade the image reconstruction due to increased data-model mismatch. Incorporating the nonactive antenna-compensation model from Part I of this paper into our hybrid element near field image reconstruction algorithm is shown to restore image quality when fixed antenna-array data acquisition is used. Improvements are most dramatic for inclusions located in near proximity to the antenna array itself, although cases of improvement in the recovery of centered heterogeneities are also illustrated. Increases in the frequency of illumination are found to warrant an increased need for nonactive antenna compensation. Quantitative measures of recovered inclusion shape and position reveal a systematic improvement in image reconstruction quality when the nonactive antenna-compensation model is employed. Improvements in electrical property value recovery of localized heterogeneities are also observed. Image reconstructions in freshly excised breast tissue illustrate the applicability of the approach when used with our two-dimensional microwave imaging system.
ASJC Scopus subject areas
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging
- Radiological and Ultrasound Technology
- Electrical and Electronic Engineering
- Computer Science Applications
- Computational Theory and Mathematics