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Fast analytical scatter estimation using graphics processing units.

Harry Ingleby1, Jonas Lippuner2, Daniel W Rickey1

  • 1Division of Medical Physics, CancerCare Manitoba, McDermot Avenue, Winnipeg, Manitoba, Canada Department of Physics and Astronomy, University of Manitoba, Winnipeg, Manitoba, Canada Department of Radiology, University of Manitoba, Winnipeg, Manitoba, Canada.

Journal of X-Ray Science and Technology
|April 18, 2015
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Summary
This summary is machine-generated.

This study introduces a fast graphics processing unit (GPU)-based analytical estimator for Compton and Rayleigh scatter in cone-beam computed tomography (CBCT). The method accurately estimates scatter, improving image quality and offering potential for scatter correction in CBCT imaging.

Keywords:
Scatter estimationcompton scattergraphics processing unitsrayleigh scatter

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Area of Science:

  • Medical Imaging Physics
  • Computational Imaging
  • Radiological Sciences

Background:

  • Scatter degrades image quality in cone-beam computed tomography (CBCT).
  • Accurate scatter estimation is crucial for effective scatter correction algorithms.
  • Patient-specific scatter modeling is computationally intensive.

Purpose of the Study:

  • To develop a rapid, patient-specific analytical estimator for first-order Compton and Rayleigh scatter in CBCT.
  • To implement the estimator using graphics processing units (GPUs) for accelerated computation.
  • To validate the estimator's performance against Monte Carlo simulations.

Main Methods:

  • An analytical estimator for Compton and Rayleigh scatter was developed for CBCT geometry.
  • The estimator was implemented using NVIDIA's CUDA for GPU execution.
  • Performance was validated against Monte Carlo simulations using numerical and anthropomorphic phantoms.
  • Qualitative and quantitative comparisons assessed the agreement between analytical and Monte Carlo estimates.

Main Results:

  • Monoenergetic analytical and Monte Carlo scatter estimates demonstrated very good agreement.
  • Good agreement was observed for Compton single scatter, and reasonable agreement for Rayleigh single scatter, compared to polyenergetic Monte Carlo estimates.
  • The analytical estimator required 669 seconds for a single projection on a specific GPU.
  • Incorporating first-order scatter improved the contrast-to-noise ratio in reconstructed images.

Conclusions:

  • The GPU-implemented analytical scatter estimator provides fast and accurate single scatter estimates.
  • Further acceleration and methods for multiple scatter are needed for practical scatter correction.
  • This method shows promise as a component of advanced scatter correction schemes in CBCT.