Dose minimization for material-selective CT with energy-selective detectors

Optimal use of data redundancies is of importance to keep image quality at a maximum and to reduce patient dose to a minimum. Energy-selective CT, as it may become widely available due to the technological advances of photon-counting energy-selective x-ray detectors, opens new possibilities for dose reduction. In this work we propose a method to minimize voxel noise in material-specific reconstructions by making use of data redundancies as they occur when the number of energy bins is larger than the number of basis materials used for material decomposition. The results of a CTDI phantom simulation study with four energy bins and two basis materials indicates almost 50% dose reduction when using all data redundancies. In the special case of only one material our noise minimization technique reduces to a simple inverse variance weighting of the energy bins.