Robust primary modulation-based scatter estimation for cone-beam CT

Med Phys. 2015 Jan;42(1):469-78. doi: 10.1118/1.4903261.

Abstract

Purpose: Scattered radiation is one of the major problems facing image quality in flat detector cone-beam computed tomography (CBCT). Previously, a new scatter estimation and correction method using primary beam modulation has been proposed. The original image processing technique used a frequency-domain-based analysis, which proved to be sensitive to the accuracy of the modulator pattern both spatially and in amplitude as well as to the frequency of the modulation pattern. In addition, it cannot account for penumbra effects that occur, for example, due to the finite focal spot size and the scatter estimate can be degraded by high-frequency components of the primary image.

Methods: In this paper, the authors present a new way to estimate the scatter using primary modulation. It is less sensitive to modulator nonidealities and most importantly can handle arbitrary modulator shapes and changes in modulator attenuation. The main idea is that the scatter estimation can be expressed as an optimization problem, which yields a separation of the scatter and the primary image. The method is evaluated using simulated and experimental CBCT data. The scattering properties of the modulator itself are analyzed using a Monte Carlo simulation.

Results: All reconstructions show strong improvements of image quality. To quantify the results, all images are compared to reference images (ideal simulations and collimated scans).

Conclusions: The proposed modulator-based scatter reduction algorithm may open the field of flat detector-based imaging to become a quantitative modality. This may have significant impact on C-arm imaging and on image-guided radiation therapy.

Publication types

  • Evaluation Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms*
  • Computer Simulation
  • Cone-Beam Computed Tomography / instrumentation
  • Cone-Beam Computed Tomography / methods*
  • Head / diagnostic imaging
  • Humans
  • Lung / diagnostic imaging
  • Models, Theoretical
  • Monte Carlo Method
  • Phantoms, Imaging
  • Scattering, Radiation*