GOAL: In K-edge tomographic imaging with photon counting detectors, the energy window width of photon counting detectors significantly affects the signal-to-noise ratio (SNR) of measured intensity data and the contrast-to-noise ratio (CNR) of reconstructed images. In this paper, we present an optimization method to determine an optimal window width around a K-edge for optimal SNR and CNR. METHODS: An objective function is designed to describe SNR of the projection data based on the Poisson distribution of detected X-ray photons. Then, a univariate optimization method is applied to obtain an X-ray energy window width. RESULTS: Numerical simulations are performed to evaluate the proposed method, and the results show that the optimal energy window width obtained from the proposed method produces not only optimal SNR data in the projection domain but also optimal CNR values in the image domain. CONCLUSION: The proposed method in the projection domain can determine an optimal energy window width for X-ray photon counting imaging, and achieve optimality in both projection and image domains. SIGNIFICANCE: Our study provides a practical way to determine the optimal energy window width of photon counting detectors, which helps improve contrast resolution for X-ray K-edge tomographic imaging.
GOAL: In K-edge tomographic imaging with photon counting detectors, the energy window width of photon counting detectors significantly affects the signal-to-noise ratio (SNR) of measured intensity data and the contrast-to-noise ratio (CNR) of reconstructed images. In this paper, we present an optimization method to determine an optimal window width around a K-edge for optimal SNR and CNR. METHODS: An objective function is designed to describe SNR of the projection data based on the Poisson distribution of detected X-ray photons. Then, a univariate optimization method is applied to obtain an X-ray energy window width. RESULTS: Numerical simulations are performed to evaluate the proposed method, and the results show that the optimal energy window width obtained from the proposed method produces not only optimal SNR data in the projection domain but also optimal CNR values in the image domain. CONCLUSION: The proposed method in the projection domain can determine an optimal energy window width for X-ray photon counting imaging, and achieve optimality in both projection and image domains. SIGNIFICANCE: Our study provides a practical way to determine the optimal energy window width of photon counting detectors, which helps improve contrast resolution for X-ray K-edge tomographic imaging.
Authors: Courtney A Coursey; Rendon C Nelson; Daniel T Boll; Erik K Paulson; Lisa M Ho; Amy M Neville; Daniele Marin; Rajan T Gupta; Sebastian T Schindera Journal: Radiographics Date: 2010 Jul-Aug Impact factor: 5.333
Authors: J P Schlomka; E Roessl; R Dorscheid; S Dill; G Martens; T Istel; C Bäumer; C Herrmann; R Steadman; G Zeitler; A Livne; R Proksa Journal: Phys Med Biol Date: 2008-07-08 Impact factor: 3.609
Authors: Yongchang Zheng; Danni Ai; Pan Zhang; Yefei Gao; Likun Xia; Shunda Du; Xinting Sang; Jian Yang Journal: PLoS One Date: 2016-11-15 Impact factor: 3.240