Adaptive and robust techniques (ART) for thermoacoustic and photoacoustic tomography

Abstract

In this paper, we present new Adaptive and Robust Techniques (ART) for microwave-based thermoacoustic tomography (TAT) and laser-based photo-acoustic tomography (PAT), and study their performances for breast cancer detection. TAT and PAT are emerging medical imaging techniques that combine the merits of high contrast due to electromagnetic or laser stimulation and high resolution offered by thermal acoustic imaging. The current image reconstruction methods used for TAT and PAT, such as the widely used Delay-and-Sum (DAS) approach, are data-independent and suffer from low resolution, high sidelobe levels, and poor interference rejection capabilities. The data-adaptive ART can have much better resolution and much better interference rejection capabilities than their data-independent counterparts. By allowing certain uncertainties, ART can be used to mitigate the amplitude and phase distortion problems encountered in TAT and PAT. Specifically, in the first step of ART, RCB is used for waveform estimation by treating the amplitude distortion with an uncertainty parameter. In the second step of ART, a simple yet effective peak searching method is used for phase distortion correction. Compared with other energy or amplitude based response intensity estimation methods, peak searching can be used to improve image quality with little additional computational costs. Moreover, since the acoustic pulse is usually bipolar: a positive peak, corresponding to the compression pulse, and a negative peak, corresponding to the rarefaction pulse, we can further enhance the image contrast in TAT or PAT by using the peak-to-peak difference as the response intensity for a focal point. The excellent performance of ART is demonstrated using both simulated and experimentally measured data.