Material reconstruction for spectral computed tomography with detector response function. (3rd October 2016)

• Record Type: Journal Article
• Authors: Liu, Jiulong; Gao, Hao
• Is Part Of: Inverse problems. Volume 32:Number 11(2016:Nov.)
• Publication Date: 2016-10-03
• Subjects: computed tomography -- sparsity regularization -- image reconstruction; Inverse problems (Differential equations) -- Periodicals; 515.357
• DOI: 10.1088/0266-5611/32/11/114001
• Languages: English
• ISSNs: 0266-5611

Abstract

Abstract: Different from conventional computed tomography (CT), spectral CT using energy-resolved photon-counting detectors is able to provide the unprecedented material compositions. However accurate spectral CT needs to account for the detector response function (DRF), which is often distorted by factors such as pulse pileup and charge-sharing. In this work, we propose material reconstruction methods for spectral CT with DRF. The simulation results suggest that the proposed methods reconstructed more accurate material compositions than the conventional method without DRF. Moreover, the proposed linearized method with linear data fidelity from spectral resampling had improved reconstruction quality from the nonlinear method directly based on nonlinear data fidelity.