Image Reconstruction of High-Quality Photoacoustic Tomography Using Wavelet-Analysis-Based Algorithm
A modified method of high-quality photoacoustic tomography reconstruction incorporates wavelet-analysis-based algorithm into filtered back-projection algorithm is proposed. According to the method, each photoacoustic signal captured by ultra-wideband transducer is decomposed into a combination of multiple wavelets to realize wide band-pass antinoise processing. The modified algorithm is successfully applied to image simulated breast tumor phantom and brain structure of a rat brain in vivo, respectively. In the reconstructed images, the extra- and intra-annulus structure of the simulated breast tumor phantom is clearly identified with effective noise suppression. The vascular network and other detailed brain structures of rat brain organization are clearly identified with the skull and scalp intact. The image spatial resolution can reach 204 microns approximately. The experimental results demonstrate that the modified method based on the wavelet-analysis-based algorithm has much higher antinoise capacity, and can greatly improve the reconstruction image quality for deeply penetrating photoacoustic tomography.