X-ray Fluorescence Computed Tomography (XFCT) Imaging with a Superfine Pencil Beam X-ray Source

X-ray fluorescence computed tomography (XFCT) is a molecular imaging technique that can be used to sense different elements or nanoparticle (NP) agents inside deep samples or tissues. However, XFCT has not been a popular molecular imaging tool because it has limited molecular sensitivity and spatial resolution. We present a benchtop XFCT imaging system in which a superfine pencil-beam X-ray source and a ring of X-ray spectrometers were simulated using GATE (Geant4 Application for Tomographic Emission) Monte Carlo software. An accelerated majorization minimization (MM) algorithm with an L1 regularization scheme was used to reconstruct the XFCT image of molybdenum (Mo) NP targets. Good target localization was achieved with a DICE coefficient of 88.737%. The reconstructed signal of the targets was found to be proportional to the target concentrations if detector number, detector placement, and angular projection number are optimized. The MM algorithm performance was compared with the maximum likelihood expectation maximization (ML-EM) and filtered back projection (FBP) algorithms. Our results indicate that the MM algorithm is superior to the ML-EM and FBP algorithms. We found that the MM algorithm was able to reconstruct XFCT targets as small as 0.25 mm in diameter. We also found that measurements with three angular projections and a 20-detector ring are enough to reconstruct the XFCT images.

Monitor Points Selection in CFD FLACS for Gas Detector Placement

Gas detector first invented was in 1815 to detect the presence of the methane gas and becomes part of a safety system when it is capable to detect the gas leakage and decrease the risk of major accident occurrence. However, the efficiency of the gas detector has been questioned among industry people due to unable to measure the effectiveness of the gas detector quantitatively. Industry people has a problem on how many and where should they locate the gas detector. This study explained the very beginning steps on how to determine the number and location of the gas detector should be installed. This research simulated the gas explosion cloud by using CFD FLACS at highly hazardous area by setting the four parameters with different values of wind speed, wind direction, leak rate and leak direction. In order to optimize the placement of the gas detector, three objectives need to be achieved: 1) to obtain the fastest response time of the gas detector to any gas leakage, 2) to ensure the availability of the gas detection system in worst conditions and 3) to place the gas detector in the potentially hazardous area. The locations of the gas detector meet the objectives based on the approach applied in this study.