Scatter removal in digital x-ray images by combined Monte Carlo and analytical techniques

The scatter point spread function (PSF) is determined for various geometries in diagnostic two dimensional projection imaging, using Monte Carlo (MC) techniques designed to take into account polychromatic spectra (at 100 kVp) and multiple scattering directions and histories. With the knowledge of the primary photon fraction, a total normalized system PSF (primary plus scatter) is derived for each case using analytical and numerical techniques. Numerical Hankel transformation of the PSF profile provides a frequency domain filter that is inverted and applied to experimentally acquired images of a homogeneous lucite phantom matching the MC simulation geometry and technique. Frequency domain processing of the scatter degraded images, followed by inverse transformation, results in images with the scatter component accurately removed in most cases, except for a DC offset. A semi-analytic neural network derived PSF is also used on experimental images, demonstrating similar results as the MC derived filter with the added benefit of time efficient implementation on a case by case basis.