(untitled) (Communications in Computational Physics, 2018)
Photoacoustic tomography is an emerging technique in biomedicine that is capable of visualizing high resolution structural and functional information of tissue up to several centimeters deep. Mesh based numerical reconstruction algorithms have an unrivaled advantage over other reconstruction algorithms in photoacoustic imaging, due to its accurate mathematical modeling and the capability to recover multiple optical/acoustic parameters in the reconstruction. However, the slow reconstruction speed and huge memory cost hindered this advanced reconstruction algorithm from application areas where large scale reconstruction or real/near-real time reconstruction is required, for example, sub-millimeter or micrometer resolution imaging, photoacoustic guided cancer treatment, etc. In this study, we reported a high performance photoacoustic tomography method based on parallel computing strategy with multiprocessor scheme. Our simulation result has shown that the parallelized photoacoustic tomography method using multiprocessor scheme is capable of providing fine reconstructed images of blood vessel structures up to 0.14mm in diameter. Further phantom experiment demonstrated that cross hairs can be clearly reconstructed, when a mesh comprised of 28512 triangle finite elements is used. Therefore, our multiprocessor based parallelized photoacoustic tomography might be promising for large scale reconstruction or real/near-real time reconstruction in biomedical application of mesh-based photoacoustic tomography algorithm.