Photoacoustic signal simulation using discrete particle approach and its application in tomography.

A theoretical framework for photoacoustic (PA) signal simulation using a discrete particle approach is discussed and tomographic image reconstruction using such signals is reported. Various numerical phantoms in two dimensions were constructed by inserting monodisperse/polydisperse solid circles/discs of uniform strength occupying regular or random locations within the imaging region. In particular, a blood vessel network phantom was simulated by positioning solid circles mimicking red blood cells randomly within the vessel using a Monte Carlo method. The PA signal from a single disc was obtained by numerically evaluating the analytical formula and then such signals from many discs were summed up linearly to generate the resultant signals at detector locations. Classical backprojection and time reversal algorithms were employed to form reconstructed images. Two model-based approaches, namely impulse response-based (IRB) and interpolation-based (IPB) methods, were also deployed for image reconstruction. Some standard parameters were calculated to assess the performance of these reconstruction algorithms. The simulation results demonstrate that the Monte Carlo method can be applied in practice for fast simulation of tissue realization keeping microscopic details intact and accordingly, PA signals can be calculated for PAT imaging. Further, the IRB technique produces images with superior quality and outperforms other algorithms.