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Register a new userImprovements in Micro-CT Method for Characterizing X-ray Monocapillary Optics
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Accurate characterization of the inner surface of X-ray monocapillary optics (XMCO) is of great significance in X-ray optics research. Compared with other characterization methods, the micro computed tomography (micro-CT) method has its unique advantages but also has some disadvantages, such as a long scanning time, long image reconstruction time, and inconvenient scanning process. In this paper, sparse sampling was proposed to shorten the scanning time, GPU acceleration technology was used to improve the speed of image reconstruction, and a simple geometric calibration algorithm was proposed to avoid the calibration phantom and simplify the scanning process. These methodologies will popularize the use of the micro-CT method in XMCO characterization.
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Traditional model-based image reconstruction (MBIR) methods combine forward and noise models with simple object priors. Recent machine learning methods for image reconstruction typically involve supervised learning or unsupervised learning, both of which have their advantages and disadvantages. In this work, we propose a unified supervised-unsupervised (SUPER) learning framework for X-ray computed tomography (CT) image reconstruction. The proposed learning formulation combines both unsupervised learning-based priors (or even simple analytical priors) together with (supervised) deep network-based priors in a unified MBIR framework based on a fixed point iteration analysis. The proposed training algorithm is also an approximate scheme for a bilevel supervised training optimization problem, wherein the network-based regularizer in the lower-level MBIR problem is optimized using an upper-level reconstruction loss. The training problem is optimized by alternating between updating the network weights and iteratively updating the reconstructions based on those weights. We demonstrate the learned SUPER models efficacy for low-dose CT image reconstruction, for which we use the NIH AAPM Mayo Clinic Low Dose CT Grand Challenge dataset for training and testing. In our experiments, we studied different combinations of supervised deep network priors and unsupervised learning-based or analytical priors. Both numerical and visual results show the superiority of the proposed unified SUPER methods over standalone supervised learning-based methods, iterative MBIR methods, and variations of SUPER obtained via ablation studies. We also show that the proposed algorithm converges rapidly in practice.
In a color X-ray camera, spatial resolution is achieved by means of a polycapillary optic conducting X-ray photons from small regions on a sample to distinct energy dispersive pixels on a CCD matrix. At present, the resolution limit of color X-ray camera systems can go down to several microns and is mainly restricted to pixel dimensions. The recent development of an efficient subpixel resolution algorithm allows a release from pixel size, limiting the resolution only to the quality of the optics. In this work polycapillary properties that influence the spatial resolution are systematized and assessed both theoretically and experimentally. It is demonstrated that with the current technological level reaching one micron resolution is challenging, but possible.
The planned HL-LHC (High Luminosity LHC) in 2025 is being designed to maximise the physics potential through a sizable increase in the luminosity up to 6*10^34 cm^-2 s^-1. A consequence of this increased luminosity is the expected radiation damage at 3000 fb^-1 after ten years of operation, requiring the tracking detectors to withstand fluences to over 1*10^16 1 MeV n_eq/cm^2 . In order to cope with the consequent increased readout rates, a complete re-design of the current ATLAS Inner Detector (ID) is being developed as the Inner Tracker (ITk). Two proposed detectors for the ATLAS strip tracker region of the ITk were characterized at the Diamond Light Source with a 3 um FWHM 15 keV micro focused X-ray beam. The devices under test were a 320 Um thick silicon stereo (Barrel) ATLAS12 strip mini sensor wire bonded to a 130 nm CMOS binary readout chip (ABC130) and a 320 Um thick full size radial (end-cap) strip sensor - utilizing bi-metal readout layers - wire bonded to 250 nm CMOS binary readout chips (ABCN-25). A resolution better than the inter strip pitch of the 74.5 um strips was achieved for both detectors. The effect of the p-stop diffusion layers between strips was investigated in detail for the wire bond pad regions. Inter strip charge collection measurements indicate that the effective width of the strip on the silicon sensors is determined by p-stop regions between the strips rather than the strip pitch.
Printed circuit boards (PCBs) are widely used in most electrical and electronic equipments or products. Hazardous substances such as Pb, Hg, Cd, etc, can be present in high concentrations in PCBs and the degradation and release of these substances poses a huge threat to humans and the environment. To investigation the chemical composition of PCBs in domestic market of China, a practical micro-focus X-ray fluorescence system is setup to make the elements analysis, especially for detecting hazardous substances. Collimator is adopted to focus the X-ray emitted from X-ray tube. BRUKER X-ray detector with proportional counter is used to detect the emitted fluorescence from the PCB samples. Both single layer PCB samples and double layers PCB samples made of epoxy glass fiber are purchased from the domestic market of China. Besides, a MC55 wireless communication module made by SIEMENS in Germany is used as the reference material. Experimental results from the fluorescence spectrums of the testing points of PCB samples show that, hazardous substances, mainly Pb and Br, are detected from the welding pads and substrates. In addition, statistical data about the average relatively amount of the main substances in testing points are also illustrated. It is verified that micro-XRF screening offers a simple and quick qualitative measurement of hazardous substances in PCBs.
We have developed a position response calibration method for a micro-channel plate (MCP) detector with a delay-line anode position readout scheme. Using an {em in situ} calibration mask, an accuracy of 8~$mu$m and a resolution of 85~$mu$m (FWHM) have been achieved for MeV-scale $alpha$ particles and ions with energies of $sim$10~keV. At this level of accuracy, the difference between the MCP position responses to high-energy $alpha$ particles and low-energy ions is significant. The improved performance of the MCP detector can find applications in many fields of AMO and nuclear physics. In our case, it helps reducing systematic uncertainties in a high-precision nuclear $beta$-decay experiment.
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