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Author Liu, J. ♦ Gao, H.
Source United States Department of Energy Office of Scientific and Technical Information
Content type Text
Language English
Subject Keyword APPLIED LIFE SCIENCES ♦ RADIATION PROTECTION AND DOSIMETRY ♦ COMPUTERIZED TOMOGRAPHY ♦ EFFICIENCY ♦ IMAGE PROCESSING ♦ NONLINEAR PROBLEMS ♦ RADIOPROTECTIVE SUBSTANCES ♦ RESPONSE FUNCTIONS ♦ SIMULATION ♦ X RADIATION
Abstract Purpose: Different from the conventional computed tomography (CT), spectral CT based on energy-resolved photon-counting detectors is able to provide the unprecedented material composition. However, an important missing piece for accurate spectral CT is to incorporate the detector response function (DRF), which is distorted by factors such as pulse pileup and charge-sharing. In this work, we propose material reconstruction methods for spectral CT with DRF. Methods: The polyenergetic X-ray forward model takes the DRF into account for accurate material reconstruction. Two image reconstruction methods are proposed: a direct method based on the nonlinear data fidelity from DRF-based forward model; a linear-data-fidelity based method that relies on the spectral rebinning so that the corresponding DRF matrix is invertible. Then the image reconstruction problem is regularized with the isotropic TV term and solved by alternating direction method of multipliers. Results: The simulation results suggest that the proposed methods provided more accurate material compositions than the standard method without DRF. Moreover, the proposed method with linear data fidelity had improved reconstruction quality from the proposed method with nonlinear data fidelity. Conclusion: We have proposed material reconstruction methods for spectral CT with DRF, whichprovided more accurate material compositions than the standard methods without DRF. Moreover, the proposed method with linear data fidelity had improved reconstruction quality from the proposed method with nonlinear data fidelity. Jiulong Liu and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).
ISSN 00942405
Educational Use Research
Learning Resource Type Article
Publisher Date 2016-06-15
Publisher Place United States
Journal Medical Physics
Volume Number 43
Issue Number 6


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