A method for stoichiometric material reconstruction with spectroscopic X-ray pixel detectors

Recent developments in X-ray detector technology provide complex electronics in each pixel. This will lead to a new generation of X-ray imaging systems measuring not only the position but also the energy of each incoming photon. Our goal is to take advantage of this additional energy information in X-ray imaging, especially in medical imaging. Therefore we developed an algorithm to reconstruct quantitative information of the object with a Maximum Likelihood Estimation (MLE) approach. The method uses vector space transformations to calculate the effective areal density for each considered material inside the object. Image fusion of the conventional image and the novel information of the material reconstruction takes advantage from both methods. This is done by superposition of the colour-coded material concentration with the gray-scale image. Enhancement of the reconstructed material images can be obtained through suppression of correlated noise: A pixel wise vector space rotation, which diagonalizes the covariance matrix, results in new, lower noise images, but at the cost of pure material information