Abstract
Current benchtop x-ray fluorescence computed tomography (XFCT) devices, which use x-ray tubes to stimulate x-ray fluorescence (XRF) photons, suffer from the contamination of Compton scatter background produced by the polychromatic incident beam. The conventional maximum-likelihood expectation-maximization (ML-EM) algorithm only considers the noise model of the XRF signal, which results in high statistical noise in reconstructed images caused by scattered photons. In this study, we proposed a scattering noise model enhanced EM-TV algorithm for benchtop XFCT image reconstruction in order to reduce the noise of scatter background and improve the sensitivity of XFCT images. The statistical noise of scattered photons was considered in the likelihood function and the EM iteration step was modified correspondingly to suppress the statistical noise caused by Compton scattered photons. The robustness of the EM iteration was improved by applying the reweighted total variation (TV) norm as the penalty function. Numerical simulations and imaging experiments of a PMMA phantom consisting of gadolinium (Gd) solutions were performed to validate the proposed algorithm. The phantom was irradiated by a cone-beam polychromatic source and the projection was recorded by a linear-array photon counting detector. For comparison, the XFCT images of Gd were reconstructed using different algorithms. Results indicate that compared with the conventional ML-EM algorithm, the proposed algorithm can obtain XFCT images with lower background noise and higher contrast, which may further improve the sensitivity and image performance of current benchtop XFCT systems.
Highlights
X-ray fluorescence computed tomography (XFCT) is an element-specific imaging modality which has recently been proposed for imaging of High-Z elements (e.g. iodine (I), barium (Ba), gadolinium (Gd) and gold (Au)) in objects
As the projection data of XFCT is acquired by detecting the x-ray fluorescent (XRF) photons emitted from the target element, background tissues will not produce XRF signal, which results in high sensitivity and contrast of XFCT when detecting fluorescence materials [1], [2]
We presented a scattering noise model enhanced EM-total variation (TV) algorithm for XFCT image reconstruction in order to further reduce the statistical noise caused by Compton scatter background
Summary
X-ray fluorescence computed tomography (XFCT) is an element-specific imaging modality which has recently been proposed for imaging of High-Z elements (e.g. iodine (I), barium (Ba), gadolinium (Gd) and gold (Au)) in objects. As the projection data of XFCT is acquired by detecting the x-ray fluorescent (XRF) photons emitted from the target element, background tissues will not produce XRF signal, which results in high sensitivity and contrast of XFCT when detecting fluorescence materials [1], [2]. The synchrotron beam is monochromatic and linear polarized, which produces XRF signal with high intensity and low scatter background [7]. Due to the limited access of synchrotron, recent studies focus more on the benchtop XFCT system using conventional x-ray tubes [8]–[10]. Two main shortcomings of current benchtop XFCT are the limited detection efficiency and the contamination of XRF signal with Compton scatter background.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
