Cuda Parallel Implementation of Image Reconstruction Algorithm for Positron Emission Tomography
| Autor: | Belzunce Ma, Verrastro Ca, Venialgo E, Cohen Im |
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| Rok vydání: | 2012 |
| Předmět: |
Computer science
Image quality Parallel algorithm Thread (computing) Iterative reconstruction Computational science Race condition law.invention CUDA Projector law Computer Science::Mathematical Software Radiology Nuclear Medicine and imaging ComputingMethodologies_COMPUTERGRAPHICS Fermi Gamma-ray Space Telescope |
| Zdroj: | The Open Medical Imaging Journal. 6:108-118 |
| ISSN: | 1874-3471 |
| DOI: | 10.2174/1874347101206010108 |
| Popis: | Although the use of iterative algorithms for image reconstruction in 3D Positron Emission Tomography (PET) has shown to produce images with better quality than analytical methods, they are computationally expensive. New Graphic Processor Units (GPUs) provide high performance at low cost and programming tools that make it possible to execute parallel algorithms in scientific applications. In this work, a GPU parallel implementation of the iterative reconstruction algorithm MLEM 3D has been developed using CUDA, a parallel model from NVIDIA. The Siddon algorithm was used as Projector and Backprojector. Acceleration factors up to 85 times were achieved, with respect to a single thread CPU implementation. The performance in GPU with Tesla and Fermi, which are respectively the first and the last generation of CUDA compatible architectures, has been compared. The image quality in each platform has been analyzed, showing a higher level of noise in GPU, due to race condition problems. The new features of Fermi architecture permitted to solve this problem using atomic operations. |
| Databáze: | OpenAIRE |
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