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Dual-energy CT has the potential to overcome many of the limitations of routine single-energy CT scanning, such a,.., the potential to provide quantitative imaging via electron density, effective atomic munber, and virtual monochromatic imaging and the potential to completely eliminate beam-hardening artifacts via projection space decomposition. While the potential clinical benefit is strong, a possible barrier to more frequent clinical use of dual-energy CT scanning is radiation dose for high quality images. While image quality in dual-energy CT depends on a munber of factors, including dose partitioning, the choice of kV pair, and the amount of pre filtration used, a munber of strategies have been employed to improve image quality in dual-energy CT. Four main methods are: (1) increa,..,e the radiation dose, (2) increase the slice thickness, (3) perform voxel averaging, or (4) use noise reduction algorithms. While these methods offer options for improving image quality, ideally, it is desirable not to have to increase radiation dose or sacrifice spatial resolution (in the x-y plane or in the z-direction). Therefore, it is the purpose of this work to investigate the application of Prior Image Constrained Compressed Sensing (PICCS) in dual-energy CT to reduce radiation dose without sacrificing image quality. In particular, we investigate the use of PICCS in dual-energy CT to generate material density images at half the radiation dose of a commonly used gemstone spectral imaging (GSI) protocol. lVIaterial density images are generated using half the radiation dose, and virtual monochromatic images are generated as a linear combination of half-dose material density images. In this abstract, qualitative and quantitative evaluation are provided to assess the performance of PICCS relative to FBP images at the full dose level and at the half dose level.
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