ABSTRACT
This chapter presents adaptive and robust methods (ARMs) based on robust Capon beamforming (RCB) for the image reconstruction of thermoacoustic tomography (TAT) and photoacoustic tomography (PAT) systems. These methods can be used to mitigate the amplitude and phase distortion problems in TAT and PAT by allowing certain uncertainties. An attractive advantage of TAT and PAT is that they possess the merits of both fine spatial resolution and good imaging contrast. The chapter also presents an investigation using a multifrequency TAT (MF-TAT) system for early breast cancer detection. By studying the microwave energy absorption properties of breast tissue and tumor, it shows that MF-TAT can offer higher signal-to-noise ratio (SNR), higher imaging contrast, and more effective clutter suppression capability than the single-frequency TAT. MF-ARM has been presented for image formation. This data-adaptive algorithm can achieve better resolution and better interference rejection capability than its data-independent counterparts, such as delay-and-sum (DAS).
