Efficient object scatter correction algorithm for third and fourth generation CT scanners

Abstract

X-ray photons which are scattered inside the object slice and reach the detector array increase the detected signal and produce image artifacts as "cupping" effects in large objects and dark bands between regions of high attenuation. The artifact amplitudes increase with scanned volume or slice width. Object scatter can be reduced in third generation computed tomography (CT) geometry by collimating the detector elements. However, a correction can still improve image quality. For fourth generation CT geometry, only poor anti-scatter collimation is possible and a numeric correction is necessary. This paper presents a correction algorithm which can be parameterized for third and fourth generation CT geometry. The method requires low computational effort and allows flexible application to different body regions by simple parameter adjustments. The object scatter intensity which is subtracted from the measured signal is calculated with convolution of the weighted and windowed projection data with a spatially invariant "scatter convolution function". The scatter convolution function is approximated for the desired scanner geometry from pencil beam simulations and measurements using coherent and incoherent differential scatter cross section data. Several examples of phantom and medical objects scanned with third and fourth generation CT systems are discussed. In third generation scanners, scatter artifacts are effectively corrected. For fourth generation geometry with poor anti-scatter collimation, object scatter artifacts are strongly reduced.

Computed Tomography and Magnetic Resonance Imaging for Noninvasive Coronary Angiography and Plaque Imaging

“…Multiple stationary detectors may be needed for greater volume coverage and higher spatial resolution. New reconstruction algorithms may reduce the cone beam-induced artifacts 24 and allow ECG-gated reconstruction from nonspiral continuous acquisition.…”

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

“…These are the transmission values of copper and air at an x-ray energy of 60 keV for a thickness of 0.23 mm. Scatter was simulated using a convolution-based scatter model 8 and added to the simulated intensity data. To demonstrate that this is a realistic simulation scenario, an additional Monte Carlo simulation of the modulator without F.…”

“…A standard approach is the insertion of an antiscatter grid, which removes a certain amount of the scattered radiation while most of the desired primary radiation reaches the detector. Other methods [1][2][3][4][5][6][7][8][9] try to compute the scatter from the image itself, either using convolutionbased approaches or even more sophisticated solutions based on Monte Carlo simulation.…”

Energy-resolved Compton scatter estimation for micro-CT

“…To enable derivation of a feasible implementation, we now follow the method of Rinkel et al'° in assuming the attenuation factor a08 is equal to that of photons scattered at 0 = 0, i.e., = exp { J t(x, ) dx} (12) where x represents position along the line connecting the source and j5, and x is the location of j5 (the detector pixel behind' v). This assumption enables the simplification rxp apreapost = exp { J (x, ) dx} (13) where I is the primary (scatter-free) x-ray intensity and the second equality arises from the Beer-Lambert Law.…”