(A) study on a scatter correction method based on thickness estimation in dual-energy radiography

Abstract

Dual energy x-ray radiography can be used to separate soft and dense-material images for medical and industrial applications. It can be performed successfully with a line-scanning system because of its scatter-free nature. With area detectors, however, scattered radiation also contributes to the signal. This undesired behavior of scattered x-ray photons in radiography causes serious degradation of contrast in observed images, and poor separation of soft- and dense-material images. The percentage of scattered photons is typically 60 % to 70 % in the lungs and 80 % to 95 % in the mediastinum for a standard PA chest radiograph. Even though anti-scatter grids can reduce the scatter fractions to 20 % to 30 % in the lungs and 40 % to 60 % in the mediastinum, dual-energy radiography requires additional scatter correction. Several methods for scatter correction have been suggested to improve results. Such methods, however, require additional lead blocks or detectors, and additional exposures to estimate the scatter fraction for every correction. Others have used only one or two convolution kernels, even though the scatter point spread functions have different shapes as a function of object thickness. A new scatter correction method in dual-energy radiography called the TB scatter correction method is suggested by this study, based on iterative thickness estimation using unique scatter point spread functions. The TB correction method uses information from a dual-energy algorithm to correct the images. In order to verify the effectiveness of this method, a set of MCNP simulation and experiment was performed. The scatter information for each combination of thickness of two materials, aluminum-water phantom in simulation and aluminum-acryl phantom in experiment, was represented in the form of a scatter point spread function. Scatter point spread functions can be either simulated, or measured and induced by Fourier transform. The way to measure the scatter point spread func...