A Dual-Energy CT (DECT) with a spectral detector greatly extends the capabilities of CT by incorporating energy-dependent information of the X-ray attenuation. In order to fully exploit DECT capabilities, it is required to perform a process known as spectral decomposition. However, this process is sensitive to noise, suffers from reduced photon count per layer in DECT scans and generates anti-correlated noise in the estimated material specific images. In order to overcome these problems, the Anti-Correlated Rudin, Osher and Fatemi (AC-ROF) model is applied for noise reduction, exploiting the relationship between the material-specific images. However, this model deteriorates the structural information with intense noise. In this paper we propose to extend this method by integrating it into an iterative reconstruction procedure to improve the noise reduction performance. The resulting algorithm is called Iterative Reconstruction AC-ROF, or IR-AC-ROF. We have tested AC-ROF and IR-AC-ROF algorithms with realistic brain simulation phantoms and show encouraging results indicating that the resulting material-specific images of IR-AC-ROF can generate better mono-energetic images with improved brain structure visibility. This demonstrates the benefit of including the noise reduction constraints within the reconstruction procedure, rather than using them in a post-processing step.
We report on the modeling, characterization, benchmarking, and optimization of an interventional cone beam CT system based on a dual layer X-ray detector by means of physics based simulations.
By Monte Carlo methods, we log the interaction and dose deposition (i.e. signal generation) of X-ray photons in the dual layer geometry, including scattering processes and fluorescence photon emission. From the spatial dose distribution inside the detection volume, we derive typical detector properties like X-ray spectral responses, detective quantum efficiencies 𝐷𝑄𝐸(0), and noise characteristics for particular detector layouts.
We apply these results in subsequent full system simulations to generate 3D imaging scans of dual layer spectral projections, for custom virtual phantoms containing inserts of e.g. blood sediment or iodine with different concentrations. These simulated images are used to calculate key performance indicators of the imaging system, like e.g. receiver operating characteristic based analysis of material separation capabilities.
In an acute stroke parts of the human brain undergo subtle physiological changes, which are often visible as hypo- or hyperdense regions in Computed Tomography (CT) images. In the case of ischemic stroke usually an edema develops due to undersupplied cells forming regions of a core (dead tissue) and a penumbra (salvable tissue). For stroke diagnosis and outcome control it is very important to know the location and size of these different kinds of damaged tissue.
We have modelled the changes in elemental composition of brain tissue in different phases of an ischemic stroke. Influence of a number of factors on the absolute Hounsfield units is investigated as possible causes of intra- and interpatient variation. The modeled pathological changes are included in different software brain models. Subsequently we have simulated X-ray images of these brain models acquired by dual energy Cone Beam Computed Tomography (CBCT). Our modelling is based on a combination of analytical and Monte-Carlo methods. As an example of spectral processing virtual monoenergetic images are reconstructed from the simulated projections.
Simulated images are intended to optimize acquisition parameters for clinical studies beforehand and to develop new image processing algorithms to enhance the diagnostic value. As example a water map is calculated to better visualize the formation of an edema after ischemic stroke.
A pixelated X-ray semiconductor detector (="direct converter") is studied which contains an inhomogeneous electric
field parallel to the depth axis caused by different concentrations of ionized dopants. X-ray energy depositions and
charge movements within the detector are modeled in Monte-Carlo simulations giving access to a statistical analysis of
electron drift times and current pulse widths for various degrees of static polarization. Charges induced on the pixel
electrodes and pulse heights are evaluated and put to histograms of spectral detector responses and pulse height spectra,
respectively, considering energy measurements before and after electronic pulse shaping. For n-doped semiconductors,
the detector performance degrades due to pulse broadening. In contrast, a moderate p-doping can improve the detector
performance in terms of shorter electron pulses, as long as the detector is not limited by dynamic polarization.
In "Spectral CT" based on energy-resolving photon-counting detectors (also "multi-energy CT") spectral information
of transmitted X-radiation is measured in order to extract additional information about the material
composition of the scanned object. Common practice is to decompose the attenuation line integrals into several
components based on models of physical (e.g. photo/Compton/K-edge) or material properties (e.g.
water/calcium). Scattered radiation causes a significant deterioration to the results, which are obtained with these
models, as the measured spectrum in a specific detector element contains additional contributions which are not
related to the attenuation in the respective line integral of the beam. In this paper the detrimental impact of
scattered radiation in multi-energy CT is quantitatively analyzed by means of Monte-Carlo simulations. Large
projection data sets of full rotational acquisitions are computed by combining noise-free analytical primary radiation
with Monte-Carlo calculated scattered radiation of high statistical accuracy. The simulations show that,
compared to the primary spectrum, the scatter spectrum is significantly shifted towards lower energies resulting
in very high scatter-to-primary ratios for energies below 50keV. In the analysis of sinograms and reconstructed
data using extended Alvarez-Macovsky decomposition into Photo-, Compton-, and K-edge images, it is revealed
that scattered radiation causes significant inhomogeneity artifacts especially in the Photo image. Additionally
"crosstalk" between Photo-, Compton- and K-edge images is found as K-edge structures appear in the other
images and vice versa. Quantitatively it is found that due to scatter the reconstructed concentration of the
K-edge material is up to 23 % smaller than its correct value.
The use of two-dimensional, focused, anti-scatter-grids (ASGs) in computed tomography is one essential solution to
reduce the scatter radiation for large area detectors.
A detailed analysis of the requirements and related image quality aspects lead to the specification of the two-dimensional
focused geometry of the X-ray absorbing grids. Scatter simulations indicated trade-off conditions and provided
estimations for the expected scatter reduction performance.
Different production technologies for focused two-dimensional structures have been evaluated. The presented
technology of Tomo Lithographic Molding (TomoTM) shows good fulfilment of the specifications. TomoTM is a synthesis
of lithographic micromachining, precision stack lamination, molding, and casting processes with application-specific
material systems. Geometry, material properties, and scatter performance have been investigated. Different analysis
methods will be presented and results of the investigations demonstrate the performance capability of this two-dimensional
Material composition of the tungsten-polymer composite, homogeneity of wall thickness, and precision of the focusing
have the biggest influence on the X-ray behavior. Dynamic forces on the anti-scatter-grid during CT operations should
not lead to dynamic shadowing or intensity modulation on the active pixel area. Simulations of the wall deformation
have been done to estimate the maximum position deviation.
Prototype two-dimensional ASGs have been characterized and show promising results.
In the framework of Spectral Computed Tomography (Spectral CT), scattered X-ray radiation is examined for its spectral
composition and spatial distribution by means of Monte Carlo simulations. A reliable material (e.g. bone / contrast agent)
separation and quantification requires a precise knowledge of the transmitted X-ray spectrum especially for low energy
photons. Unfortunately, for lower energies the primary intensity is increasingly covered by scattered radiation. The
detected scattered radiation can be classified into two main categories with respect to their scattering history. The first
category contains purely Rayleigh or one-time Compton scattered photons which typically have small scattering angles
and an energy spectrum similar to that of the transmitted primary radiation. The second category comprises multiple
Compton scattered photons with a spectral composition which is typically softer than that of the transmitted primary
photons. In regions of strong beam attenuation (i.e. in the X-ray shadow of a scanned object), the scattered radiation is
mainly composed of multiple Compton scattered photons. As a consequence, the spectrally resolved scatter-to-primary
ratios strongly increase at low energies. High-quality anti-scatter grids can be used to reduce especially the detection of
multiple Compton-scattered photons. A quantitative evaluation of measured photon energies below a certain limit
between 30 keV and 50 keV (depending on the phantom geometry and the applied anti-scatter grid) is challenging, since
primary photons are superposed by a significantly higher amount of scattered photons.
In Computed Tomography (CT), the image quality sensitively depends on the accuracy of the X-ray projection signal, which is acquired by a two-dimensional array of pixel cells in the detector. If the signal of X-ray photons is spread out to neighboring pixels (crosstalk), a decrease of spatial resolution may result. Moreover, streak and ring artifacts may emerge. Deploying system simulations for state-of-the-art CT detector configurations, we characterize origin and appearance of these artifacts in the reconstructed CT images for different scenarios. A uniform pixel-to-pixel crosstalk results in a loss of spatial resolution only. The Modulation Transfer Function (MTF) is attenuated, without affecting the limiting resolution, which is defined as the first zero of the MTF. Additional streak and ring artifacts appear, if the pixel-to-pixel crosstalk is non-uniform. Parallel to the system simulations we developed an analytical model. The model explains resolution loss and artifact level using the first and second derivative of the X-ray profile acquired by the detector. Simulations and analytical model are in agreement to each other. We discuss the perceptibility of ring and streak artifacts within noisy images if no crosstalk correction is applied.