Deconvolution algorithms for photoacoustic tomography to reduce blurring caused by finite sized detectors

Most reconstruction algorithms for photoacoustic tomography, like back-projection or time-reversal, work ideally for point-like detectors. For real detectors, which integrate the pressure over their finite size, it was shown that images reconstructed by back-projection or time-reversal show some blurring. Iterative reconstruction algorithms using an imaging matrix can take the finite size of real detectors directly into account, but the numerical effort is significantly higher compared to the use of direct algorithms. For spherical or cylindrical detection surfaces the blurring caused by a finite detector size is proportional to the distance from the rotation center (“spin blur”) and is equal to the detector size at the detection surface. In this work we use deconvolution algorithms to reduce this type of blurring on simulated and on experimental data. Experimental data were obtained on a plastisol cylinder with 6 thin holes filled with an absorbing liquid (OrangeG). The holes were located on a spiral emanating from the center of the cylinder. Data acquisition was done by utilization of a piezoelectric detector which was rotated around the plastisol cylinder.