Broadband ultrasound signals will produce distortion in viscoacoustic medium, which may influence the accuracy of time-of-flight (TOF) measurement. Under the condition of single-frequency acoustic source, the wave propagation process in viscoacoustic medium was analyzed and an approximate solution of the wave propagation was given. Instances of broadband ultrasound were analyzed and simulated based on the single-frequency results. A single-frequency matching pursuits (SFMP) algorithm was then introduced to solve the waveform distortion problem. Time-frequency decomposition was applied to extracting the single-frequency compositions from broadband ultrasound signals, and then these compositions were sent to the matching pursuits (MP) algorithm for calculating the TOF parameters. Compared with the broadband signals, the shapes of extracted single-frequency signals change more slightly as distance and attenuation coefficient increase. The residuals of SFMP were far less than those of MP algorithm. Experimental results show that the SFMP algorithm is able to eliminate waveform distortion of broadband ultrasound in viscoacoustic medium, which helps improve the accuracy of TOF measurement.
The photoacoustic tomography （PAT） method, based on compressive sensing （CS） theory, requires that, for the CS reconstruction, the desired image should have a sparse representation in a known transform domain. However, the sparsity of photoacoustic signals is destroyed because noises always exist. Therefore, the original sparse signal cannot be effectively recovered using the general reconstruction algorithm. In this study, Bayesian compressive sensing （BCS） is employed to obtain highly sparse representations of photoacoustic images based on a set of noisy CS measurements. Results of simulation demonstrate that the BCS-reconstructed image can achieve superior performance than other state-of-the-art CS-reconstruction algorithms.
