Estimation of the optimal parameters for K-edge subtraction imaging with PixiRad-2/PixieIII photon counting detector on a conventional laboratory X-ray micro-tomograph

Photon Counting Detectors (PCDs) open new opportunities in X-ray imaging. Pixie III is a PCD using simultaneously two energy thresholds. This enables to acquire images from two distinct energy bins in a single exposure. This is particularly suited to perform K-Edge Subtraction (KES) imaging with laboratory sources. In that context, one has however to deal with an energy bin optimization: narrow energy bins leads to high KES signal, at the expense of higher noise, while wider energy bins leads to poor KES signal but better statistics. This work presents a model that aims at finding the optimal thresholds and source voltage in order to retrieve the best Contrast to Noise Ratio (CNR) for a given sample. The model also optimizes the configurations for conventional absorption modality and compares both modalities. We noticed that the input flux and the energy difference between the thresholds influence the noise on image. We included this in the model using phenomenological laws. The model is then compared to empirical optimization by experimental screening of the parameters on model materials composed of barium, iodine and water. Finally, a study of the predicted CNRs has function of the sample composition is presented as an example of usage of the model