9 March 2017 X-ray spectral calibration from transmission measurements using Gaussian blur model
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In recent years, there has been a resurgence of interest towards spectral computed tomography (CT) driven by a growing demand in photon-counting detectors. In performing spectral CT scanning, a practical issue is to accurately calibrate the spectral response of the X-ray imaging system. Mis-calibrated detector elements can lead to strong ring artifacts in the reconstructed tomographic image. For the purpose of modeling the spectral response, we propose a Gaussian blur model combined with the prior information on the X-ray spectra that accurately predicts the transmission curve and at the same time recovers realistic estimate of the spectra. This proposed method uses a low dimensional representation of the X-ray spectra by enforcing a sparsity constraint on the parameters of the Gaussian blur model. These parameters are estimated by formulating a constrained optimization problem, and two algorithms are suggested to solve such problem in an efficient way. The effectiveness of the model is evaluated on the simulated transmission measurements of known thicknesses of known materials. The performance of the two algorithms are also compared through the error between estimated and model X-ray spectra and the error between the predicted and simulated transmission curves.
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Wooseok Ha, Wooseok Ha, Emil Y. Sidky, Emil Y. Sidky, Rina Foygel Barber, Rina Foygel Barber, } "X-ray spectral calibration from transmission measurements using Gaussian blur model", Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101323D (9 March 2017); doi: 10.1117/12.2254406; https://doi.org/10.1117/12.2254406

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