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Accelerating reconstruction of reference digital tomosynthesis using graphics hardware.

Hui Yan1, Lei Ren, Devon J Godfrey

  • 1Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710, USA. hui.yan@duke.edu

Medical Physics
|November 8, 2007
PubMed
Summary
This summary is machine-generated.

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Accelerating digital tomosynthesis (DTS) image reconstruction for image-guided radiation therapy (IGRT) is crucial. A new GPU-based algorithm significantly speeds up digitally reconstructed radiograph (DRR) generation, making DTS reference images clinically practical.

Area of Science:

  • Medical Physics
  • Radiotherapy Technology
  • Image Processing

Background:

  • Digital tomosynthesis (DTS) is vital for image-guided radiation therapy (IGRT).
  • Fast DTS image reconstruction is essential for clinical implementation.
  • Reference DTS images require digitally reconstructed radiographs (DRRs) from planning CT, which are slow to generate.

Purpose of the Study:

  • To develop and evaluate a high-performance algorithm for DRR reconstruction.
  • To accelerate the generation of reference DTS images for IGRT.
  • To assess the clinical practicality of hardware-accelerated DRR reconstruction.

Main Methods:

  • Implemented a high-performance DRR reconstruction algorithm on a graphics processing unit (GPU).
  • Compared the GPU-based algorithm with the conventional software-based ray-casting algorithm.

Related Experiment Videos

  • Evaluated DTS image reconstruction using DRRs generated by both methods.

    • Main Results:

    • The GPU-based DRR reconstruction achieved an average efficiency improvement of 67 times over the software method.
    • Image quality of DRRs generated by the hardware method was comparable to the software method.
    • Accelerated DRR reconstruction significantly reduced the overall time for reference DTS image generation.

    Conclusions:

    • Hardware-accelerated DRR reconstruction is clinically practical for IGRT.
    • This advancement facilitates faster DTS image reconstruction for target localization.
    • The developed algorithm enhances the efficiency of image-guided radiation therapy workflows.