Benchtop x-ray fluorescence computed tomography (XFCT) imaging

Ignacio O. Romero; Yile Fang; Michael Lun; Changqing Li

doi:10.1117/12.2584577

15 February 2021 Benchtop x-ray fluorescence computed tomography (XFCT) imaging

Ignacio O. Romero, Yile Fang, Michael Lun, Changqing Li

Proceedings Volume 11600, Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging; 1160015 (2021) https://doi.org/10.1117/12.2584577
Event: SPIE Medical Imaging, 2021, Online Only

Abstract

X-ray fluorescence computed tomography (XFCT) is a molecular imaging technique of x-ray photons, which can be used to sense different elements or nanoparticle (NP) agents inside deep samples or tissues. XFCT has been an active research topic for many years. However, XFCT has not been a popular molecular imaging tool because it has limited molecular sensitivity and spatial resolution. To further investigate XFCT imaging, we present a benchtop XFCT imaging system, in in which a unique pencil beam x-ray source and a ring of x-ray spectrometers were simulated using GATE (Geant4 Application for Tomographic Emission) software. An accelerated majorization minimization (MM) algorithm with an L¹ regularization scheme was used to reconstruct the XRF image of Molybdenum (Mo) NP targets from the numerical measurements of GATE simulations. With a low x-ray source output rate, good target localization was achieved with a DICE coefficient of 83.681%. The reconstructed signal intensity of the targets was found to be relatively proportional to the target concentrations if detector number and placement is optimized. The MM algorithm performance was compared with maximum likelihood expectation maximization (ML-EM) and filtered back projection (FBP) algorithms. In the future, the benchtop XFCT imaging system will be tested experimentally.

Conference Presentation

Citation Download Citation

Ignacio O. Romero, Yile Fang, Michael Lun, and Changqing Li "Benchtop x-ray fluorescence computed tomography (XFCT) imaging", Proc. SPIE 11600, Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1160015 (15 February 2021); https://doi.org/10.1117/12.2584577

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