Empirical scatter correction (esc): A new CT scatter correction method and its application to metal artifact reduction

Scatter artifacts impair the CT image quality and the accuracy of CT values. Especially in cases with metal implants and in wide cone-angle flat detector CT scans, scatter artifact removal can be of great value. Typical scatter correction methods try to estimate scattered radiation and subtract the estimated scatter from the uncorrected data. Scatter is found either by time-consuming Monte Carlo-based simulations of the photon trajectories, or by rawdata-based modelling of the scatter content using scatter kernels, whose open parameters have to be determined very accurately and for each scanner and type of object individually, and that sometimes even require a data base of typical objects. The procedures are time-consuming and require intimate knowledge about the scanner, in particular about the spectral properties, for which a correction is designed. We propose an empirical scatter correction (ESC) algorithm which does not need lots of prior knowledge for calibration. ESC assumes that a linear combination of the uncorrected image with various ESC basis images is scatter-free. The coefficients for the linear combination are determined in image domain by maximizing a flatness criterion of the combined volume. Here, we minimized the total variation in soft tissue regions using the gradient descent method with a line search. Simulated data and several patient data sets acquired with a clinical cone-beam spiral CT scanner, where scatter was added using a Monte Carlo scatter calculation algorithm, were used to evaluate ESC. Metal implants were simulated into those data sets, too. Our preliminary results indicate that ESC has the potential to efficiently reduce scatter artifacts in general, and metal artifacts in particular. ESC is computationally inexpensive, highly flexible, and does not require know-how of the scanner properties.