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In principle, differential phase contrast (DPC) imaging allows the use of a hospital grade x-ray tube that has a large focal
spot size and a wide polychromatic spectrum. It should be noted that due to the integration of interference patterns over
the entire spectrum, the fringe contrast in the final intensity image is lower than that from a monochromatic spectrum.
Therefore better image quality should be potentially obtained if the energy-dependent interference patterns can be
analyzed separately. The key idea of the proposed spectral DPC imaging approach is to acquire DPC images for each
photon energy channel, which is named spectral DPC images. The final DPC image can be computed by summing up
these spectral DPC images or just computed using certain 'color' representation algorithms to enhance desired features.
This research is a feasibility study based on computer simulations to investigate how the spectral DPC method works for
a DPC-based cone beam CT (DPC-CBCT) system. The spectral DPC imaging approach is applied to an x-ray spectral
centered at 30keV, which is divided into four energy channels in simulation. A simple numerical phantom with low
contrast inserts is used and the entire imaging process is simulated using Fresnel diffraction theory. Phase stepping
approach is used to manifest and retrieve phase information. The phantom is scanned over a full circular trajectory and
the Hilbert filter-based FBP algorithm is used to compute the DPC-CBCT reconstruction. The reconstruction from the
proposed spectral DPC-CBCT is compared to that from the conventional DPC-CBCT that only takes detector images for
the integrated polychromatic spectrum. The uniformity, noise level and contrast of the inserts in the reconstruction are
measured and compared. Simulation results indicate that the spectral DPC imaging approach can improve object contrast and reduce noise for DPC-CBCT.
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