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Dual energy imaging has made it possible to enhance contrast in medical images using images containing different energy information, by combining low and high energy images. Dual energy data can either be acquired using double exposures or splitting the energy spectrum into two images using one exposure. This thesis presents investigations of dual energy imaging using a detector solution developed by XCounter which provides dual energy images in a single exposure with a threshold separating low and high energy images. Phantom experiments with phantoms of aluminum and plexiglas were performed using weighted logarithmic subtraction and basis material decomposition to produce dual energy images. Methods were validated and images were evaluated in terms of signal difference in noise ratio to find the threshold and tube voltage combination for optimum energy spectrum separation. The methods were also tested on biological materials using bone, soft tissue and iodine solution as contrast enhancer, to investigate K-edge imaging.  Optimal separation of plexiglas and aluminum were found at 70 kVp and the threshold parameter set within a range of 8 to 9, which corresponds to approximately 30 to 34 keV. For K-edge imaging, the optimum separation were found close to K-edge energy of iodine. The results found in the phantom study correlated with results from the biological material study.

The goal of this research is to contribute to the development of MARS spectral CT and to demonstrate the feasibility of molecular imaging using the technology. MARS is a newly developed micro CT scanner, incorporating the latest spectroscopic Medipix photon counting detector. I show that the scanner can identify both drug markers and stenosis of atherosclerosis labelled with non-toxic nanoparticles. I also show that spectral computed tomography using Medipix x-ray detectors can give quantitative measurements of concentrations of gold nanoparticles in phantoms, mice and excised atheroma. The characterisation of the Medipix2 assemblies with Si and CdTe x-ray sensors using poly-energetic x-ray sources has been performed. I measure the inhomogeneities within the sensors; individual pixel sensitivity response; and their saturation effects at higher photon fluxes. The effects of charge sharing on the performance of Medipix2 have been assessed, showing that it compromises energy resolution much more than spatial resolution. I have commissioned several MARS scanners incorporating several different Medipix2 and Medipix3 cameras. After the characterization of x-ray detectors and the geometrical assessment of MARS-CT, spectral CT data has been acquired, using x-ray energies that are appropriate for human imaging. The outcome shows that MARS scanner has the ability to discriminate among low atomic number materials, and from various concentrations of heavy atoms. This new imaging modality, used with functionalized gold nanoparticles, gives a new tool to assess plaque vulnerability. I demonstrated this by using gold nanoparticles, attached to antibodies, which targeted to thrombotic events in excised plaque. Likewise, the imaging modality can be used to track drugs labelled with any heavy atoms to assess how much drug gets into a target organ. Thus the methodology could be used to accelerate development of new drug treatments for cancers and inflammatory diseases.

The Large Ultraviolet/Optical/Infrared Surveyor (LUVOIR) is one of four large mission concepts currently undergoing community study for consideration by the 2020 Astronomy and Astrophysics Decadal Survey. LUVOIR is being designed to pursue an ambitious program of exoplanetary discovery and characterization, cosmic origins astrophysics, and planetary science. The LUVOIR study team is investigating two large telescope apertures (9- and 15-meter primary mirror diameters) and a host of science instruments to carry out the primary mission goals. Many of the exoplanet, cosmic origins, and planetary science goals of LUVOIR require high-throughput, imaging spectroscopy at ultraviolet (100 - 400 nm) wavelengths. The LUVOIR Ultraviolet Multi-Object Spectrograph, LUMOS, is being designed to support all of the UV science requirements of LUVOIR, from exoplanet host star characterization to tomography of circumgalactic halos to water plumes on outer solar system satellites. LUMOS offers point source and multi-object spectroscopy across the UV bandpass, with multiple resolution modes to support different science goals. The instrument will provide low (R = 8,000 - 18,000) and medium (R = 30,000 - 65,000) resolution modes across the far-ultraviolet (FUV: 100 - 200 nm) and near-ultraviolet (NUV: 200 - 400 nm) windows, and a very low resolution mode (R = 500) for spectroscopic investigations of extremely faint objects in the FUV. Imaging spectroscopy will be accomplished over a 3 x 1.6 arcminute field-of-view by employing holographically-ruled diffraction gratings to control optical aberrations, microshutter arrays (MSA) built on the heritage of the Near Infrared Spectrograph (NIRSpec) on the James Webb Space Telescope (JWST), advanced optical coatings for high-throughput in the FUV, and next generation large-format photon-counting detectors. The spectroscopic capabilities of LUMOS are augmented by an FUV imaging channel (100 - 200nm, 13 milliarcsecond angular resolution, 2 x 2 arcminute field-of-view) that will employ a complement of narrow-and medium-band filters. The instrument definition, design, and development are being carried out by an instrument study team led by the University of Colorado, Goddard Space Flight Center, and the LUVOIR Science and Technology Definition Team. LUMOS has recently completed a preliminary design in Goddard's Instrument Design Laboratory and is being incorporated into the working LUVOIR mission concept. In this proceeding, we describe the instrument requirements for LUMOS, the instrument design, and technology development recommendations to support the hardware required for LUMOS. We present an overview of LUMOS' observing modes and estimated performance curves for effective area, spectral resolution, and imaging performance. Example "LUMOS 100-hour Highlights" observing programs are presented to demonstrate the potential power of LUVOIR's ultraviolet spectroscopic capabilities.

Contrast agents are often crucial in medical imaging for disease diagnosis. Novel contrast agents, such as gold nanoparticles (AuNPs) and lanthanides, are being ex- plored for a variety of clinical applications. Preclinical testing of these contrast agents is necessary before being approved for use in humans, which requires the use of small animal imaging techniques. Small animal imaging demands the detection of these contrast agents in trace amounts at acceptable imaging time and radiation dose. Two such imaging techniques include x-ray fluorescence computed tomography (XFCT) and photon-counting CT (PCCT). XFCT combines the principles of CT with x-ray fluorescence by detecting fluorescent x-rays from contrast agents at various projections to reconstruct contrast agent maps. XFCT can image trace amounts of AuNPs but is limited to small animal imaging due to fluorescent x-ray attenuation and scatter. PCCT uses photon-counting detectors that separate the CT data into energy bins. This enables contrast agent detection by recognizing the energy dependence of x-ray attenuation in different materials, independent of AuNP depth, and can provide anatomical information that XFCT cannot. To achieve the best of both worlds, we modeled and built a table-top x-ray imaging system capable of simultaneous XFCT and PCCT imaging. We used Monte Carlo simulation software for the following work in XFCT imaging of AuNPs. We simulated XFCT induced by x-ray, electron, and proton beams scanning a small animal-sized object (phantom) containing AuNPs with Monte Carlo techniques. XFCT induced by x-rays resulted in the best image quality of AuNPs, however high-energy electron and medium-energy proton XFCT may be feasible for on-board x-ray fluorescence techniques during radiation therapy. We then simulated a scan of a phantom containing AuNPs on a table-top system to optimize the detector arrangement, size, and data acquisition strategy based on the resulting XFCT image quality and available detector equipment. To enable faster XFCT data acquisition, we separately simulated another AuNP phantom and determined the best collimator geometry for Au fluorescent x-ray detection. We also performed experiments on our table-top x-ray imaging system in the lab. Phantoms containing multiples of three lanthanide contrast agents were scanned on our tabletop x-ray imaging system using a photon-counting detector capable of sustaining high x-ray fluxes that enabled PCCT. We used a novel subtraction algorithm for reconstructing separate contrast agent maps; all lanthanides were distinct at low concentrations including gadolinium and holmium that are close in atomic number. Finally, we performed the first simultaneous XFCT and PCCT scan of a phantom and mice containing both gadolinium and gold based on the optimized parameters from our simulations. This dissertation outlines the development of our tabletop x-ray imaging system and the optimization of the complex parameters necessary to obtain XFCT and PCCT images of multiple contrast agents at biologically-relevant concentrations. / Graduate

<p dir="ltr">X-ray computed tomography (CT) based on photon counting detectors (PCD) extends standard CT by counting detected photons in multiple energy bins. PCD data can be used to increase the contrast-to-noise ratio (CNR), increase spatial resolution, reduce radiation dose, reduce injected contrast dose, and compute a material decomposition using a specified set of basis materials [1]. Current commercial and prototype clinical photon counting CT systems utilize PCD-CT reconstruction methods that either reconstruct from each spectral bin separately, or first create an estimate of a material sinogram using a specified set of basis materials and then reconstruct from these material sinograms. However, existing methods are not able to utilize simultaneously and in a modular fashion both the measured spectral information and advanced prior models in order to produce a material decomposition. </p><p dir="ltr">We describe an efficient, modular framework for PCD-based CT reconstruction and material decomposition using Multi-Agent Consensus Equilibrium (MACE). Portions of this dissertation appear in [2]. Our method employs a detector proximal map or agent that uses PCD measurements to update an estimate of the path length sinogram. We also create a prior agent in the form of a sinogram denoiser that enforces both physical and empirical knowledge about the material-decomposed sinogram. The sinogram reconstruction is computed using the MACE algorithm, which finds an equilibrium solution between the two agents, and the final image is reconstructed from the estimated sinogram. Importantly, the modularity of our method allows the two agents to be designed, implemented, and optimized independently. Our results on simulated data show a substantial (2-3 times) noise reduction vs conventional maximum likelihood reconstruction when applied to a phantom used to evaluate low contrast detectability. Our results with measured data show an even higher reduction (2-12 times) in noise standard deviation. Lastly, we demonstrate our method on a Lungman phantom that more realistically represents the human body. </p>

During the past years photon-counting detectors (PCDs) have emerged as an alternative to conventional energy-integrating detectors and may significantly improve the standard of care for computed tomography (CT). There are two main alternatives for the material of the detector: cadmium telluride (CdTe) and silicon (Si). The settings of the X-ray tube and the applied filters need to be evaluated and optimized for the new detector technology. In this report, Monte Carlo simulations are used to determine how image quality is affected by different X-ray tube voltages and filter thicknesses. The image quality indicators that were chosen to evaluate are detective quantum efficiency (DQE) for material quantification and both DQE and dose-normalized signal-difference-to-noise ratio (SDNR) for detection tasks. Overall, silicon-based detectors performed better than cadmium-based detectors for quantification imaging tasks for all object thicknesses, while cadmium-based detectors were superior for detection imaging tasks in larger patients. For both silicon- and cadmium-based detectors, the dose-normalized image quality was largely independent of filter thickness, while the X-ray tube voltage had a more distinct impact on the result, where low voltages were optimal. / Under de senaste åren har fotonräknande detektorer blivit aktuellt som ett alternativ till konventionella energiintegrerande detektorer och kommer troligen förbättra datortomografibilder avsevärt. För de nya detektorerna finns det två huvudsakliga materialalternativ: kadmiumtellurid (CdTe) och kisel (Si). Inställningarna för röntgenröret och det pålagda filtret behöver utvärderas och optimeras för den nya detektorteknologin. I denna rapport användes Monte Carlo-simuleringar för att bestämma hur bildkvaliteten påverkades av rörspänningen och filtertjockleken. Bildkvaliteten bestämdes sedan utifrån tre indikatorer, detective quantum efficiency (DQE) för materialbestämning samt både DQE och dosnormaliserad signal-difference-to-noise ratio (SDNR) för detektionsuppgifter.    Den kiselbaserade detektorn presterade bättre än den kadmiumbaserade för materialbestämning för alla patientstorlekar medan den kadmiumbaserade presterade bättre på detektionsuppgifterna för större patienter. Vidare var den dosnormaliserade bildkvaliteten för både kisel- och kadmiumdetektorer svagt beroende av filtertjocklek medan båda påverkades starkt av rörspänningen, där låga spänningar var att föredra.