Virtual non-contrast (VNC) CT images derived from multi-energy CT data have demonstrated many valuable clinical applications. However, VNC CT has not yet established itself as a technology that can reliably replace the true non-contrast CT. One commonly observed phenomenon is an erroneous removal or reduction of calcium signal in VNC images. The purpose of this work is to develop a photon counting CT-based method to decouple the iodine signal from the calcium signal to achieve VNC CT imaging. Thanks to the energy resolving capability of the photon counting detector (PCD), a photon counting CT enables all single kV CT data to carry additional spectral information needed for VNC CT reconstruction. However, the energy discriminating capability of a real PCD system is far from ideal, which can severely degrade the fidelity of the encoded spectral information and the efficiency of the material decomposition. In this work, a physics-based model of the PCD energy response function was developed and experimentally validated. By leveraging this model, a method was developed to correct the distorted spectral information in the measured PCD energy bin data, allowing the true post image object spectrum to be estimated to accomplish accurate three-material decomposition and VNC CT reconstruction. Both numerical simulation and experimental results demonstrated that the proposed spectral distortion correction method can effectively improve the CT number accuracy of both iodine-containing vessels and calcium-containing bony structures in VNC CT images.
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