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Mapping iterative medical imaging algorithm on cell accelerator.

Meilian Xu1, Parimala Thulasiraman

  • 1Department of Computer Science, University of Manitoba, Winnipeg, MB, Canada R3T 2N2.

International Journal of Biomedical Imaging
|September 17, 2011
PubMed
Summary
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This study optimized the OS-SART algorithm for the Cell Broadband Engine (Cell BE) architecture. The parallel computing approach significantly speeds up image reconstruction, making it viable for commercial CT machines.

Area of Science:

  • Medical Imaging
  • Computer Science

Background:

  • Algebraic reconstruction techniques (ART) offer reduced radiation dose compared to Fourier backprojection.
  • OS-SART (ordered subset simultaneous ART) provides faster convergence and good image quality but suffers from long processing times.
  • Parallel computing on heterogeneous multicore architectures can enhance medical imaging algorithm performance.

Purpose of the Study:

  • To map and optimize the OS-SART algorithm on the Cell Broadband Engine (Cell BE) architecture.
  • To overcome the computational challenges of OS-SART for commercial CT applications.
  • To evaluate the performance improvements achieved through parallelization on Cell BE.

Main Methods:

  • The OS-SART algorithm was mapped onto the Cell BE architecture, leveraging its PowerPC Processor Element (PPE) and Synergetic Processor Elements (SPEs).

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  • Optimization techniques were developed to address the limited memory on SPEs and facilitate efficient data transfer.
  • Performance was evaluated by comparing the Cell BE implementation against a CPU version on a shared memory machine.

    • Main Results:

    • The Cell BE implementation achieved a five-fold speedup compared to an AMD Opteron dual-core processor.
    • Performance scaled with the number of SPEs utilized.
    • The mapping demonstrated efficient utilization of Cell BE's architectural features.

    Conclusions:

    • Parallel implementation of OS-SART on the Cell BE significantly accelerates image reconstruction.
    • The optimized Cell BE version offers a practical solution for reducing CT scan times and radiation dose.
    • Further performance gains are achievable by tuning parameters like the number of subsets and SPEs.