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A new methodology is proposed to mitigate the high computation cost required to derive accurate Monte Carlo (MC) based system matrix for tomographic image reconstruction. The strategy consists of taking advantage of the symmetries between the lines of response to increase the statistics of data collected for the determination of the system matrix coefficients. By using the rotation and axial symmetries of a cylindrical camera, the number of MC generated events can be reduced substantially without affecting the matrix coefficient accuracy. Moreover, using the GATE simulator list-mode saving capabilities for storing coincidence events, single events and/or single hits with all their relevant information, the MC simulation can be performed only once and system matrices for different system configurations be derived from the same simulation. Using for example Positron emission tomography (PET), the processing of the collected MC data can be fine tuned to the imaging system characteristics by setting accordingly the time and energy blurring, the detector efficiencies, the coincidence time window width and the energy thresholds. The system matrix can also include or exclude PET events like scatters and randoms. Furthermore, the system matrix can be computed for different image grids and basis functions without requiring a new MC simulation to be performed.