Hybrid Deterministic-Stochastic Modeling of X-Ray Beam Bowtie Filter Scatter on a CT System

Abstract

Knowledge of scatter generated by bowtie filter (i.e. x-ray beam compensator) is crucial for providing artifact free images on the CT scanners. Our approach is to use a hybrid deterministic-stochastic simulation to estimate the scatter level generated by a bowtie filter made of a material with low atomic number. First, major components of CT systems, such as source, flat filter, bowtie filter, body phantom, are built into a 3D model. The scattered photon fluence and the primary transmitted photon fluence are simulated by MCNP a Monte Carlo simulation toolkit. The rejection of scattered photon by the post patient collimator (anti-scatter grid) is simulated with an analytical formula. The biased sinogram is created by superimposing scatter signal generated by the simulation onto the primary x-ray beam signal. Finally, images with artifacts are reconstructed with the biased signal. The effect of anti-scatter grid height on scatter rejection are also discussed and demonstrated.

Department(s)

Nuclear Engineering and Radiation Science

Keywords and Phrases

Atoms; Bandpass filters; Intelligent systems; Light scattering; Monte Carlo methods; Neutron emission; Photons; Scattering; Stochastic models; Stochastic systems; X rays; Analytical formulas; Anti-scatter grids; Bowtie filters; Deterministic methods; Hybrid deterministic; Primary X-ray beams; Scattered photons; Stochastic simulations; Computerized tomography; Artifact; Computer assisted tomography; Computer simulation; Human; Image processing; Imaging phantom; Markov chain; Procedures; Artifacts; Computer Simulation; Humans; Image Processing; Computer-Assisted; Phantoms; Imaging; Stochastic Processes; Tomography; X-Ray Computed; Monte Carlo simulation; Scatter

International Standard Serial Number (ISSN)

0895-3996

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2015 IOS Press, All rights reserved.

Publication Date

01 Sep 2015

PubMed ID

26409426

Link to Full Text

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