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Modelling the penumbra in Computed Tomography1.

Audrey Kueh¹, Jason M Warnett², Gregory J Gibbons²

¹Statistics Department, University of Warwick, Warwick, UK.

Journal of X-Ray Science and Technology

|May 28, 2016

Summary

This summary is machine-generated.

A mixture model accurately quantifies computed tomography (CT) image blurring by simulating X-ray spot geometry. This approach improves image precision and helps estimate CT artifacts.

Keywords:

Computed tomography focal spot nonlinear least squares penumbra secondary radiation

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Area of Science:

Medical Imaging
Radiological Physics

Background:

Computed tomography (CT) image quality is significantly impacted by X-ray spot geometry, leading to artifacts like the penumbra effect.
The penumbra effect causes poorly defined edges in reconstructed CT volumes, degrading image precision.

Purpose of the Study:

To develop and validate a penumbra model derived from Beer's law for CT.
To confirm X-ray spot geometry using penumbra data and quantify image blurring.

Main Methods:

Two spot geometry models were investigated: a single Gaussian spot and a mixture model (Gaussian plus uniform spot).
Penumbra data was used to fit the proposed models and assess their accuracy in representing spot geometry.

Main Results:

The single Gaussian spot model showed a poor fit at the boundary of the penumbra.
The mixture model, incorporating a uniform spot, demonstrated a significantly improved fit.
Parameters for the uniform spot remained consistent across different power settings, suggesting it emits low-energy X-rays.

Conclusions:

The mixture model effectively quantifies image blurring and confirms spot geometry in CT.
Image precision can be estimated by analyzing the penumbra effect.
Employing a thin copper filter can effectively reduce the penumbra size, enhancing image quality.