High Performance 3D PET Reconstruction Using Spherical Basis Functions on a Polar Grid.

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Author
Cabello, J; Gillam, JE; Rafecas, MDate
2012Source Title
International Journal of Biomedical ImagingPublisher
Hindawi LimitedUniversity of Melbourne Author/s
Gillam, JohnAffiliation
Centre for Youth Mental HealthMetadata
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Journal ArticleCitations
Cabello, J., Gillam, J. E. & Rafecas, M. (2012). High Performance 3D PET Reconstruction Using Spherical Basis Functions on a Polar Grid.. Int J Biomed Imaging, 2012, pp.452910-. https://doi.org/10.1155/2012/452910.Access Status
Open AccessOpen Access at PMC
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3323846Abstract
Statistical iterative methods are a widely used method of image reconstruction in emission tomography. Traditionally, the image space is modelled as a combination of cubic voxels as a matter of simplicity. After reconstruction, images are routinely filtered to reduce statistical noise at the cost of spatial resolution degradation. An alternative to produce lower noise during reconstruction is to model the image space with spherical basis functions. These basis functions overlap in space producing a significantly large number of non-zero elements in the system response matrix (SRM) to store, which additionally leads to long reconstruction times. These two problems are partly overcome by exploiting spherical symmetries, although computation time is still slower compared to non-overlapping basis functions. In this work, we have implemented the reconstruction algorithm using Graphical Processing Unit (GPU) technology for speed and a precomputed Monte-Carlo-calculated SRM for accuracy. The reconstruction time achieved using spherical basis functions on a GPU was 4.3 times faster than the Central Processing Unit (CPU) and 2.5 times faster than a CPU-multi-core parallel implementation using eight cores. Overwriting hazards are minimized by combining a random line of response ordering and constrained atomic writing. Small differences in image quality were observed between implementations.
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