Various methods for discovering the location of radio frequency (RF) emitters using unmanned aerial vehicles (UAVs)
have been the focus of research over the past several years. Our work is aimed at determining the effectiveness of lowaccuracy
direction finding (DF) technology to locate RF emissions using multiple UAVs. Small, commercial-off-theshelf
(COTS) antenna systems can provide a rough estimate of an emitter's location within a 90 degree or 45 degree
sector. Using these DF systems, a team of inexpensive UAVs can be deployed to collect low-accuracy data from
multiple positions. A ground station would combine the information. In contrast to typical angle-of-arrival (AOA)
methods, this unique technique does not require precise antenna arrays, complex hardware, or significant processing
time to locate RF emissions. We present simulation results that show that accurate geolocation of emitters is possible
with DF systems using only low accuracy (90-20 degrees) Angle of Arrival (AOA) information.
The material specificity of computed tomography is quantified using an experimental benchtop imaging system
and a physics-based system model. The apparatus is operated with different detector and system configurations each
giving X-ray energy spectral information but with different overlap among the energy-bin weightings and noise
statistics. Multislice, computed tomography sinograms are acquired using dual kVp, sequential source filters or a
detector with two scintillator/photodiodes layers. Basis-material and atomic number images are created by first
applying a material decomposition algorithm followed by filtered backprojection. CT imaging of phantom materials
with known elemental composition and density were used for model validation. X-ray scatter levels are measured with a
beam-blocking technique and the impact to material accuracy is quantified. The image noise is related to the intensity
and spectral characteristics of the X-ray source. For optimal energy separation adequate image noise is required. The
system must be optimized to deliver the appropriate high mA at both energies. The dual kVp method supports the
opportunity to separately engineer the photon flux at low and high kvp. As a result, an optimized system can achieve
superior material specificity in a system with limited acquisition time or dose. In contrast, the dual-layer and sequential
acquisition modes rely on a material absorption mechanism that yields weaker energy separation and lower overall
A convolution model of scatter that is adaptable to rapid simulation and correction algorithms is tested against the measured scatter profiles. In the simple case of a uniform acrylic sheet, the convolution approach yields about 10% absolute agreement with the measured scatter profile. However, significant qualitative differences are demonstrated for phantoms with non-uniform thickness or composition. For example, the scatter profile is dependent on a bone's vertical position in the phantom whereas the primary is unchanged. Similarly, a cusp shape in the scatter profile observed near the abrupt edge of an acrylic sheet is not produced in the convolution model. An alternate approach that calculates the scatter as a 3D integral over the object volume can reproduce this behavior.
We present the analysis of the accuracy and precision of dual energy material basis decomposition for the quantification of tissue fat content in computed tomography. We compare the benefits of a pre-reconstruction (sinogram-based) dual energy imaging technique versus a post-reconstruction (image) based dual energy decomposition technique using a numerical simulation. A phantom containing plastics of known composition is measured to validate the technique. The accuracy of the image based dual energy decomposition technique is contingent on the amount of beam hardening encountered in the phantom. The accuracy of the pre-reconstruction dual energy technique depends on how accurately the system spectral response can be modeled. In both cases the precision of the dual energy imaging is determined by the photon flux.
The purpose of this paper is to investigate the use of electron-beam Computed Tomography (EBCT) dual energy scanning for improved differentiation of calcified coronary arteries from iodinated-contrasted blood, in fast moving cardiac vessels. The dual energy scanning technique can lead to an improved cardiac examination in a single breath hold with more robust calcium scoring and better vessel characterization. Dual energy can be used for material discrimination in CT imaging to differentiate materials with similar CT number, but different material attenuation properties. Mis-registration is the primary source of error in a dual energy application, since acquisitions have to be made at each energy, and motion between the acquisitions causes inconsistencies in the decomposition algorithm, which may lead to artifacts in the resultant images. Using EBCT to quickly switch x-ray source peak voltage potential (kVp), the mis-registration of patient anatomy is minimized since acquisitions at both energy spectra are completed in one study at the same cardiac phase. Two protocols for scanning the moving heart using EBCT were designed to minimize registration issues. Material basis function decomposition was used to differentiate regions containing calcium and iodine in the image. We find that this protocol is superior to CT imaging at one energy spectrum in discriminating calcium from contrast-enhanced lumen. Using dual energy EBCT scanning can enable accurate calcium scoring, and angiography applications to be performed in one exam.
Dose is becoming increasingly important for computed tomography clinical practice. It is of general interest to understand the impact that system design can have on dose and image quality. This study addresses the effect of bowtie shape on the dose and contrast-to-noise across the field of view. Simulation of the CT acquisition is used to calculate the energy deposition throughout a numerical phantom for a set of relevant system operating parameters and bowtie shapes. Mean absorbed dose is calculated by summing over the phantom volume and is compared with other typical dose specifications. A more aggressive attenuation profile of the bowtie which offers higher attenuation in the periphery of the field of view can offer the benefit of lower dose but at the expense of reduced contrast-to-noise at the edge of the cross-sectional image.
In addition to a conventional Computed Tomography (CT) image, dual energy (dual kVp) imaging can be used to generate an image of the same anatomy that represents the equivalent density of a particular material, for example, calcium, iodine, water, etc. This image can be used to improve the differentiation of materials as well as improve the accuracy of absolute density measurements in a cross-sectional image. It is important to understand the certainty of the estimation of the density of the material. Both simulations and measurements are used to quantify these errors. Data are acquired using a flat-panel based volumetric CT system, by taking two scans and adjusting the maximum energy of the source spectrum (kVp). Physics based simulations are used to compare with the measurements. After validating the simulation algorithms, the accuracy of the dual kVp method is determined using the simulations in a perturbation study.
A framework for rapid and reliable design of Volumetric Computed Tomography (VCT) systems is presented. This work uses detailed system simulation tools to model standard and anthropomorphic phantoms in order to simulate the CT image and choose optimal system specifications. CT systems using small-pitch, 2-D flat area detectors, initially developed for x-ray projection imaging, have been proposed to implement Volume CT for clinical applications. Such systems offer many advantages, but there are also many trade-offs not fully understood that affect image quality. Although many of these effects have been studied in the literature for traditional CT applications, there are unique interactions for very high-resolution flat-panel detectors that are proposed for volumetric CT. To demonstrate the process we describe an example that optimizes the parameters to achieve high detectability for thin slices. The VCT system was modeled over a range of operating parameters, including: tube voltage, tube current, tube focal spot size, detector cell size, number of views, and scintillator thickness. The response surface, which captures the effects of system components on image quality, was calculated. Optimal and robust designs can be achieved by determining an operating point from the response equations, given the constraints. We verify the system design with images from standard and low contrast phantoms. Eventually this design tool could be used, in conjunction with clinical researchers, to specify VCT scanner designs, optimize imaging protocols, and quantify image accuracy and repeatability.