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In a clinical setting, the accurate representation of pathologies and anatomical structures in CT reconstructions is important for diagnostic and therapeutical interventions. However, the presence of metal within the patient can cause significant streak artifacts within the reconstruction, possibly degrading or obscuring features within a region of interest to the imaging study. Spectral CT can be utilized to better resolve the attenuation properties of different materials and hence provide more accurate reconstructions of images. In addition, accurately modeling the polyenergetic transmission of x-ray photons, the noise properties of the data, and undersampling caused by materials with high photon attenuation can address some of the artifacts caused by metal. Previous work using a one-step image reconstruction algorithm (cOSSCIR), demonstrated the potential to remove metal artifacts caused by beam hardening and photon starvation, but streaks due to the high gradient around the boundary of metal remained. Within this framework, an accurate model of the detector geometry can be leveraged to further address metal artifacts in the reconstructed image. In this study, we investigate errors caused by “partial-volume” effects using photon-counting CT phantom simulations. Noiseless 2D fan-beam data was first generated from a pelvic phantom with bilateral hip prostheses, where each detector element was modeled as having a finite aperture using multiple ‘raylets.’ The cOSSCIR framework was modified to incorporate the nonlinear partial volume (NLPV) model based on raylets. Basis images were reconstructed by cOSSCIR with and without the NLPV model. The simulation results demonstrated that cOSSCIR with the NLPV model was able to accurately tom with metal, therefore removing metal artifacts caused by beam hardening and nonlinear partial volume effects.
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