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3 October 2016 Comparison studies of different regularizers for spectral computed tomography
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The development of energy-resolving photon-counting detectors makes it possible to collect data in different energy bins. These detectors lead to emerging spectral computed tomography (CT), which is also called multi-energy CT, energy-selective CT, color CT, etc. Spectral CT can provide additional information in comparison with conventional CT in which energy integrating detectors are used to form polychromatic projection of an object being investigated. The photon counting detectors in spectral CT can acquire projections of the object in different energy levels as they are able to reliably distinguish the received photon energies. In recent years, different methods have been developed to acquire additional information hidden in different energy levels of spectral CT images. Different regularization methods have been adopted for reconstructing the noisy image in the last decade. In this work, we numerically evaluate the performance of different regularizers such as total variation, Huber, non-local means and anisotropic diffusion regularization in spectral CT. The goal is to provide some practical guidance to accurately reconstruct the attenuation distribution of each energy channel of the spectral CT data.
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Morteza Salehjahromi, Yanbo Zhang, and Hengyong Yu "Comparison studies of different regularizers for spectral computed tomography", Proc. SPIE 9967, Developments in X-Ray Tomography X, 99671T (3 October 2016);

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