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Graphical Processing Unit based Implementations of Crystal Identification Algorithms
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 183 - Number 43 |
| Year of Publication: 2021 |
| Authors: M. Sayed, A. Arafa, H.I. Saleh |
10.5120/ijca2021921833
|
M. Sayed, A. Arafa, H.I. Saleh . Graphical Processing Unit based Implementations of Crystal Identification Algorithms. International Journal of Computer Applications. 183, 43 ( Dec 2021), 12-16. DOI=10.5120/ijca2021921833
Abstract
Crystal identification (CI) provides a solution for parallax error that occurs within the Positron Emission Tomography (PET) scanners. The CI rate is one of the main challenges to reconstruct the image in PET system. This paper proposed a high rate CI algorithm based on fractional Fourier transform (FRFT) and a powerful classifier that is Support Vector Machine (SVM). The computation of the proposed algorithm is significantly reduced to a single weighted sum of pulse’s samples. In addition, the computations were accelerated using two different approaches; Compute Unified Device Architecture (CUDA) or multi-threading high-level parallelism model (openMP) in order to satisfy a high rate for processing the scintillation pulses of PET systems. A huge number of scintillation pulses (100 000 pulses from LSO-LuYAP crystals) were processed to take full advantage of the hardware speeding up provided by a parallel implementation on a graphics processing unit (GPU). The event rates of openMP are 13 or 76 M events/s on a serial single core or parallel 8 cores processor respectively. On the other hand, the pulses were processed using Tesla K20 GPU at 942 M events/sec. The proposed implementations provide a high-speed rate of scintillation pulses that enables the designers of PET systems to increase the number of detectors for high-resolution PET images.
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