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

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    6
    Author
    Cabello, J; Gillam, JE; Rafecas, M
    Date
    2012
    Source Title
    International Journal of Biomedical Imaging
    Publisher
    Hindawi Limited
    University of Melbourne Author/s
    Gillam, John
    Affiliation
    Centre for Youth Mental Health
    Metadata
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    Document Type
    Journal Article
    Citations
    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 Access
    URI
    http://hdl.handle.net/11343/255922
    DOI
    10.1155/2012/452910
    Open Access at PMC
    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3323846
    Abstract
    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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