Cone-Beam X-ray Luminescence Computed Tomography Based on X-ray Absorption Dosage

Tianshuai Liu, Junyan Rong, Peng Gao, Wenlei Liu, Hongbing Lu


Published in:Fully3D 2017 Proceedings


X-ray luminescence computed tomography, X-ray imaging, image reconstruction
Based on X-ray excitable particles, cone-beam X-ray luminescence computed tomography (CB-XLCT) has been proposed recently, which aims to achieve high-sensitivity optical imaging as well as high spatial resolution X-ray imaging. Currently, the imaging model of most XLCT systems is derived from the intensity distribution of X-ray within the object, not completely reflecting the nature of X-ray excitation process and X-ray scattering. To further improve the imaging quality of CB-XLCT, in this study, an imaging model based on X-ray absorption dosage is proposed. As the inverse problem is seriously ill-conditioned, an adaptive Tikhonov Regularization method is used for image reconstruction of CB-XLCT. Imaging experiments with numerical simulations and a physical phantom indicate that when compared with the model based on X-ray intensity, the proposed model based on X-ray dosage improves the image quality of CB-XLCT significantly.
Tianshuai Liu
The Fourth Military Medical University
Junyan Rong
The Fourth Military Medical University
Peng Gao
The Fourth Military Medical University
Wenlei Liu
The Fourth Military Medical University
Hongbing Lu
The Fourth Military Medical University
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