Spread Spectrum Photoacoustic Tomography With Image Optimization.

Photoacoustic tomography (PAT) of biological tissue offers potential advantages in distinguishing different structures according to their chemical composition. However, as medical photoacoustic (PA) signals are broad band, which usually cover a 0.2-50 MHz range, current band-limited ultrasound transducers can only receive and present a limited fraction of that range. Besides, the received PA signals are usually of low signal-to-noise ratio (SNR), which further deteriorates the image quality. Therefore, the goal of this work is to recover the out-of-band frequency components in the received PA signals based on a best estimate of the frequency response of the ultrasound transducers, and to improve the PA image quality. Hereby, we came up with a method including signal recovery based on inverse filtering and multi-sampled signal de-noising, with which we were capable of rebuilding wider band PA signals and reconstructing PA images with higher SNR. In this way, detailed information that used to be buried in the background noise was revealed, and the boundaries of the imaging object were enhanced. Computer simulations as well as phantom and in vivo experiments were carried out and reconstructed images were given for illustration. In the future, our work can be applied to clinical and preclinical biomedical imaging fields, such as multi-spectrum PA imaging, angiography and other related fields.