Abstract
Monte Carlo is an important and well established research tool used in emission tomography. While used extensively in research applications, these techniques are not typically implemented clinically due to their low detection efficiency and long acquisition times. In order to make this computational tool faster, the variance reduction technique known as convolution-based forced detection (CFD) has been implemented into the SIMIND MC code (CFD-SIMIND) by our group. Briefly, at each site of interaction within the object, photons are forced to travel in a direction perpendicular to the detector and are then convolved with a distance dependent blurring kernel specific to that collimator and photon energy. A similar CFD method has already been implemented as an option in the SIMIND Monte Carlo program. This study performs a comparison between a well established, non-VRT Monte Carlo program, GATE, with our accelerated CFD-SIMIND. The intent of this work is to establish if CFD-SIMIND can either replace or be used in conjunction with GATE in order to gain significant reduction in simulation times for low and medium energy isotopes. A number of simulation studies were performed using point sources in air and water, along with the 3D XCAT phantom and a rectangular sheet source for 99mTc with low and medium energy collimator and 111In with medium energy collimator. A comparison in the projection domain was then performed in terms of spatial resolution, sensitivity, image profiles and energy spectra. The study has shown percent differences of between 3–5 % in sensitivity between CFD-SIMIND and GATE with mean universal image quality index value of 0.994 ± 0.009 and spatial resolution within 0.2 mm of each other. CFD-SIMIND offers a significant reduction in simulation time by a factor of 5–6 orders of magnitude compared to GATE. This acceleration time is useful for many applications. This study also provides an objective tool that can help to determine if CFD-SIMIND can be used in place of GATE in order to achieve images of sufficient quality within a reduced time and at much lower computational cost.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have