986 resultados para X-ray technique
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X-ray photoemission spectroscopy (XPS) is one of the most universal and powerful tools for investigation of chemical states and electronic structures of materials. The application of hard x-rays increases the inelastic mean free path of the emitted electrons within the solid and thus makes hard x-ray photoelectron spectroscopy (HAXPES) a bulk sensitive probe for solid state research and especially a very effective nondestructive technique to study buried layers.rnThis thesis focuses on the investigation of multilayer structures, used in magnetic tunnel junctions (MTJs), by a number of techniques applying HAXPES. MTJs are the most important components of novel nanoscale devices employed in spintronics. rnThe investigation and deep understanding of the mechanisms responsible for the high performance of such devices and properties of employed magnetic materials that are, in turn, defined by their electronic structure becomes feasible applying HAXPES. Thus the process of B diffusion in CoFeB-based MTJs was investigated with respect to the annealing temperature and its influence on the changes in the electronic structure of CoFeB electrodes that clarify the behaviour and huge TMR ratio values obtained in such devices. These results are presented in chapter 6. The results of investigation of the changes in the valence states of buried off-stoichiometric Co2MnSi electrodes were investigated with respect to the Mn content α and its influence on the observed TMR ratio are described in chapter 7.rnrnMagnetoelectronic properties such as exchange splitting in ferromagnetic materials as well as the macroscopic magnetic ordering can be studied by magnetic circular dichroism in photoemission (MCDAD). It is characterized by the appearance of an asymmetry in the photoemission spectra taken either from the magnetized sample with the reversal of the photon helicity or by reversal of magnetization direction of the sample when the photon helicity direction is fixed. Though recently it has been widely applied for the characterization of surfaces using low energy photons, the bulk properties have stayed inaccessible. Therefore in this work this method was integrated to HAXPES to provide an access to exploration of magnetic phenomena in the buried layers of the complex multilayer structures. Chapter 8 contains the results of the MCDAD measurements employing hard x-rays for exploration of magnetic properties of the common CoFe-based band-ferromagnets as well as half-metallic ferromagnet Co2FeAl-based MTJs.rnrnInasmuch as the magnetoresistive characteristics in spintronic devices are fully defined by the electron spins of ferromagnetic materials their direct measurements always attracted much attention but up to date have been limited by the surface sensitivity of the developed techniques. Chapter 9 presents the results on the successfully performed spin-resolved HAXPES experiment using a spin polarimeter of the SPLEED-type on a buried Co2FeAl0.5Si0.5 magnetic layer. The measurements prove that a spin polarization of about 50 % is retained during the transmission of the photoelectrons emitted from the Fe 2p3/2 state through a 3-nm-thick oxide capping layer.rn
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In der Erdöl– und Gasindustrie sind bildgebende Verfahren und Simulationen auf der Porenskala im Begriff Routineanwendungen zu werden. Ihr weiteres Potential lässt sich im Umweltbereich anwenden, wie z.B. für den Transport und Verbleib von Schadstoffen im Untergrund, die Speicherung von Kohlendioxid und dem natürlichen Abbau von Schadstoffen in Böden. Mit der Röntgen-Computertomografie (XCT) steht ein zerstörungsfreies 3D bildgebendes Verfahren zur Verfügung, das auch häufig für die Untersuchung der internen Struktur geologischer Proben herangezogen wird. Das erste Ziel dieser Dissertation war die Implementierung einer Bildverarbeitungstechnik, die die Strahlenaufhärtung der Röntgen-Computertomografie beseitigt und den Segmentierungsprozess dessen Daten vereinfacht. Das zweite Ziel dieser Arbeit untersuchte die kombinierten Effekte von Porenraumcharakteristika, Porentortuosität, sowie die Strömungssimulation und Transportmodellierung in Porenräumen mit der Gitter-Boltzmann-Methode. In einer zylindrischen geologischen Probe war die Position jeder Phase auf Grundlage der Beobachtung durch das Vorhandensein der Strahlenaufhärtung in den rekonstruierten Bildern, das eine radiale Funktion vom Probenrand zum Zentrum darstellt, extrahierbar und die unterschiedlichen Phasen ließen sich automatisch segmentieren. Weiterhin wurden Strahlungsaufhärtungeffekte von beliebig geformten Objekten durch einen Oberflächenanpassungsalgorithmus korrigiert. Die Methode der „least square support vector machine” (LSSVM) ist durch einen modularen Aufbau charakterisiert und ist sehr gut für die Erkennung und Klassifizierung von Mustern geeignet. Aus diesem Grund wurde die Methode der LSSVM als pixelbasierte Klassifikationsmethode implementiert. Dieser Algorithmus ist in der Lage komplexe geologische Proben korrekt zu klassifizieren, benötigt für den Fall aber längere Rechenzeiten, so dass mehrdimensionale Trainingsdatensätze verwendet werden müssen. Die Dynamik von den unmischbaren Phasen Luft und Wasser wird durch eine Kombination von Porenmorphologie und Gitter Boltzmann Methode für Drainage und Imbibition Prozessen in 3D Datensätzen von Böden, die durch synchrotron-basierte XCT gewonnen wurden, untersucht. Obwohl die Porenmorphologie eine einfache Methode ist Kugeln in den verfügbaren Porenraum einzupassen, kann sie dennoch die komplexe kapillare Hysterese als eine Funktion der Wassersättigung erklären. Eine Hysterese ist für den Kapillardruck und die hydraulische Leitfähigkeit beobachtet worden, welche durch die hauptsächlich verbundenen Porennetzwerke und der verfügbaren Porenraumgrößenverteilung verursacht sind. Die hydraulische Konduktivität ist eine Funktion des Wassersättigungslevels und wird mit einer makroskopischen Berechnung empirischer Modelle verglichen. Die Daten stimmen vor allem für hohe Wassersättigungen gut überein. Um die Gegenwart von Krankheitserregern im Grundwasser und Abwässern vorhersagen zu können, wurde in einem Bodenaggregat der Einfluss von Korngröße, Porengeometrie und Fluidflussgeschwindigkeit z.B. mit dem Mikroorganismus Escherichia coli studiert. Die asymmetrischen und langschweifigen Durchbruchskurven, besonders bei höheren Wassersättigungen, wurden durch dispersiven Transport aufgrund des verbundenen Porennetzwerks und durch die Heterogenität des Strömungsfeldes verursacht. Es wurde beobachtet, dass die biokolloidale Verweilzeit eine Funktion des Druckgradienten als auch der Kolloidgröße ist. Unsere Modellierungsergebnisse stimmen sehr gut mit den bereits veröffentlichten Daten überein.
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High-pressure powder X-ray diffraction is a fundamental technique for investigating structural responses to externally applied force. Synchrotron sources and two-dimensional detectors are required. In contrast to this conventional setup, high-resolution beamlines equipped with one-dimensional detectors could offer much better resolved peaks but cannot deliver accurate structure factors because they only sample a small portion of the Debye rings, which are usually inhomogeneous and spotty because of the small amount of sample. In this study, a simple method to overcome this problem is presented and successfully applied to solving the structure of an L-serine polymorph from powder data. A comparison of the obtained high-resolution high-pressure data with conventional data shows that this technique, providing up to ten times better angular resolution, can be of advantage for indexing, for lattice parameter refinement, and even for structure refinement and solution in special cases.
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The first objective of this study was to determine normative digital X-ray radiogrammetry (DXR) values, based on original digital images, in a pediatric population (aged 6-18 years). The second aim was to compare these reference data with patients suffering from distal radius fractures, whereas both cohorts originated from the same geographical region and were evaluated using the same technical parameters as well as inclusion and exclusion criteria. DXR-BMD and DXR-MCI of the metacarpal bones II-IV were assessed on standardized digital hand radiographs, without printing or scanning procedures. DXR parameters were estimated separately by gender and among six age groups; values in the fracture group were compared to age- and gender-matched normative data using Student's t tests and Z scores. In the reference cohort (150 boys, 138 girls), gender differences were found in bone mineral density (DXR-BMD), with higher values for girls from 11 to 14 years and for boys from 15 to 18 years (p < 0.05). Girls had higher normative metacarpal index (DXR-MCI) values than boys, with significant differences at 11-14 years (p < 0.05). In the case-control investigation, the fracture group (95 boys, 69 girls) presented lower DXR-BMD at 15-18 years in boys and 13-16 years in girls vs. the reference cohort (p < 0.05); DXR-MCI was lower at 11-18 years in boys and 11-16 years in girls (p < 0.05). Mean Z scores in the fracture group for DXR-BMD were -0.42 (boys) and -0.46 (girls), and for DXR-MCI were -0.51 (boys) and -0.53 (girls). These findings indicate that the fully digital DXR technique can be accurately applied in pediatric populations ≥ 6 years of age. The lower DXR-BMD and DXR-MCI values in the fracture group suggest promising early identification of individuals with increased fracture risk, without the need for additional radiation exposure, enabling the initiation of prevention strategies to possibly reduce the incidence of osteoporosis later in life.
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The observation of light metal ions in nucleic acids crystals is generally a fortuitous event. Sodium ions in particular are notoriously difficult to detect because their X-ray scattering contributions are virtually identical to those of water and Na+…O distances are only slightly shorter than strong hydrogen bonds between well-ordered water molecules. We demonstrate here that replacement of Na+ by K+, Rb+ or Cs+ and precise measurements of anomalous differences in intensities provide a particularly sensitive method for detecting alkali metal ion-binding sites in nucleic acid crystals. Not only can alkali metal ions be readily located in such structures, but the presence of Rb+ or Cs+ also allows structure determination by the single wavelength anomalous diffraction technique. Besides allowing identification of high occupancy binding sites, the combination of high resolution and anomalous diffraction data established here can also pinpoint binding sites that feature only partial occupancy. Conversely, high resolution of the data alone does not necessarily allow differentiation between water and partially ordered metal ions, as demonstrated with the crystal structure of a DNA duplex determined to a resolution of 0.6 Å.
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An assay that allows measurement of absolute induction frequencies for DNA double-strand breaks (dsbs) in defined regions of the genome and that quantitates rejoining of correct DNA ends has been used to study repair of dsbs in normal human fibroblasts after x-irradiation. The approach involves hybridization of single-copy DNA probes to Not I restriction fragments separated according to size by pulsed-field gel electrophoresis. Induction of dsbs is quantitated from the decrease in the intensity of the hybridizing restriction fragment and an accumulation of a smear below the band. Rejoining of dsbs results in reconstitution of the intact restriction fragment only if correct DNA ends are joined. By comparing results from this technique with results from a conventional electrophoresis assay that detects all rejoining events, it is possible to quantitate the misrejoining frequency. Three Not I fragments on the long arm of chromosome 21 were investigated with regard to dsb induction, yielding an identical induction rate of 5.8 X 10(-3) break per megabase pair per Gy. Correct dsb rejoining was measured for two of these Not I fragments after initial doses of 80 and 160 Gy. The misrejoining frequency was about 25% for both fragments and was independent of dose. This result appears to be representative for the whole genome as shown by analysis of the entire Not I fragment distribution. The correct rejoining events primarily occurred within the first 2 h, while the misrejoining kinetics included a much slower component, with about half of the events occurring between 2 and 24 h. These misrejoining kinetics are similar to those previously reported for production of exchange aberrations in interphase chromosomes.
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Thesis (Ph.D.)--University of Washington, 2016-06
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Slag composition determines the physical and chemical properties as well as the application performance of molten oxide mixtures. Therefore, it is necessary to establish a routine instrumental technique to produce accurate and precise analytical results for better process and production control. In the present paper, a multi-component analysis technique of powdered metallurgical slag samples by X-ray Fluorescence Spectrometer (XRFS) has been demonstrated. This technique provides rapid and accurate results, with minimum sample preparation. It eliminates the requirement for a fused disc, using briquetted samples protected by a layer of Borax(R). While the use of theoretical alpha coefficients has allowed accurate calibrations to be made using fewer standard samples, the application of pseudo-Voight function to curve fitting makes it possible to resolve overlapped peaks in X-ray spectra that cannot be physically separated. The analytical results of both certified reference materials and industrial slag samples measured using the present technique are comparable to those of the same samples obtained by conventional fused disc measurements.
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Analysis of intra- and inter-phase distribution of modifying elements in aluminium-silicon alloys is difficult due to the low concentrations used. This research utilises a mu-XRF (X-ray fluorescence) technique at the SPring-8 synchrotron radiation facility X-ray source and reveals that the modifying element strontium segregates exclusively to the eutectic silicon phase and the distribution of strontium within this phase is relatively homogeneous. This has important implications for the fundamental mechanisms of eutectic modification in hypoeutectic aluminium-silicon alloys. (c) 2006 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
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Photo-electron spectroscopy as an analytical tool has only received limited interest in the field of mineral science. Photo-electron spectroscopy, together with Auger electron spectroscopy, gives information about the positions of the energy levels in atoms or molecules. Application of this technique on solid materials will result in information of the band structure of these materials. The principle of photo electron spectroscopy is rather simple: photons with certain energy (wavelength) are allowed to collide with an atom, molecule or a solid material. These photons can then interact with electrons present in the atoms and one of these electrons can be excited from its orbital resulting in a situation similar to a free electron plus a positively charged atom or molecule.
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We report the formation and structural properties of co-crystals containing gemfibrozil and hydroxy derivatives of t-butylamine H2NC(CH3)3-n(CH2OH)n, with n=0, 1, 2 and 3. In each case, a 1:1 co-crystal is formed, with transfer of a proton from the carboxylic acid group of gemfibrozil to the amino group of the t-butylamine derivative. All of the co-crystal materials prepared are polycrystalline powders, and do not contain single crystals of suitable size and/or quality for single crystal X-ray diffraction studies. Structure determination of these materials has been carried out directly from powder X-ray diffraction data, using the direct-space Genetic Algorithm technique for structure solution followed by Rietveld refinement. The structural chemistry of this series of co-crystal materials reveals well-defined structural trends within the first three members of the family (n=0, 1, 2), but significantly contrasting structural properties for the member with n=3. © 2007 Elsevier Inc. All rights reserved.
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The present work describes the development of a proton induced X-ray emission (PIXE) analysis system, especially designed and builtfor routine quantitative multi-elemental analysis of a large number of samples. The historical and general developments of the analytical technique and the physical processes involved are discussed. The philosophy, design, constructional details and evaluation of a versatile vacuum chamber, an automatic multi-sample changer, an on-demand beam pulsing system and ion beam current monitoring facility are described.The system calibration using thin standard foils of Si, P, S,Cl, K, Ca, Ti, V, Fe, Cu, Ga, Ge, Rb, Y and Mo was undertaken at proton beam energies of 1 to 3 MeV in steps of 0.5 MeV energy and compared with theoretical calculations. An independent calibration check using bovine liver Standard Reference Material was performed. The minimum detectable limits have been experimentally determined at detector positions of 90° and 135° with respect to the incident beam for the above range of proton energies as a function of atomic number Z. The system has detection limits of typically 10- 7 to 10- 9 g for elements 14
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We have used a recently developed x-ray structural microscopy technique to make nondestructive, submicron-resolution measurements of the deformation microstructure below a 100mN maximum load Berkovich nanoindent in single crystal Cu. Direct observations of plastic deformation under the indent were obtained using a ~0.5 µm polychromatic microbeam and diffracted beam depth profiling to make micron-resolution spatially-resolved x-ray Laue diffraction measurements. The local lattice rotations underneath the nanoindent were found to be heterogeneous in nature as revealed by geometrically necessary dislocation (GND) densities determined for positions along lines beneath a flat indent face and under the sharp Berkovich indent blade edges. Measurements of the local rotation-axes and misorientation-angles along these lines are discussed in terms of crystallographic slip systems.
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X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.
A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.
Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.
The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).
First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.
Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.
Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.
The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.
To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.
The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.
The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.
Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.
The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.
In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.
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Spectral CT using a photon counting x-ray detector (PCXD) shows great potential for measuring material composition based on energy dependent x-ray attenuation. Spectral CT is especially suited for imaging with K-edge contrast agents to address the otherwise limited contrast in soft tissues. We have developed a micro-CT system based on a PCXD. This system enables full spectrum CT in which the energy thresholds of the PCXD are swept to sample the full energy spectrum for each detector element and projection angle. Measurements provided by the PCXD, however, are distorted due to undesirable physical eects in the detector and are very noisy due to photon starvation. In this work, we proposed two methods based on machine learning to address the spectral distortion issue and to improve the material decomposition. This rst approach is to model distortions using an articial neural network (ANN) and compensate for the distortion in a statistical reconstruction. The second approach is to directly correct for the distortion in the projections. Both technique can be done as a calibration process where the neural network can be trained using 3D printed phantoms data to learn the distortion model or the correction model of the spectral distortion. This replaces the need for synchrotron measurements required in conventional technique to derive the distortion model parametrically which could be costly and time consuming. The results demonstrate experimental feasibility and potential advantages of ANN-based distortion modeling and correction for more accurate K-edge imaging with a PCXD. Given the computational eciency with which the ANN can be applied to projection data, the proposed scheme can be readily integrated into existing CT reconstruction pipelines.