Neural-network-directed alignment of optical systems using the laser-beam spatial filter as an example

This report describes an effort at NASA Lewis Research Center to use artificial neural networks to automate the alignment and control of optical measurement systems. Specifically, it addresses the use of commercially available neural network software and hardware to direct alignments of the common laser-beam-smoothing spatial filter. The report presents a general approach for designing alignment records and combining these into training sets to teach optical alignment functions to neural networks and discusses the use of these training sets to train several types of neural networks. Neural network configurations used include the adaptive resonance network, the back-propagation-trained network, and the counter-propagation network. This work shows that neural networks can be used to produce robust sequencers. These sequencers can learn by example to execute the step-by-step procedures of optical alignment and also can learn adaptively to correct for environmentally induced misalignment. The long-range objective is to use neural networks to automate the alignment and operation of optical measurement systems in remote, harsh, or dangerous aerospace environments. This work also shows that when neural networks are trained by a human operator, training sets should be recorded, training should be executed, and testing should be done in a manner that does not depend on intellectual judgments of the human operator

Analytical, experimental, and Monte Carlo system response matrix for pinhole SPECT reconstruction

PURPOSE: To assess the performance of two approaches to the system response matrix (SRM) calculation in pinhole single photon emission computed tomography (SPECT) reconstruction. METHODS: Evaluation was performed using experimental data from a low magnification pinhole SPECT system that consisted of a rotating flat detector with a monolithic scintillator crystal. The SRM was computed following two approaches, which were based on Monte Carlo simulations (MC-SRM) and analytical techniques in combination with an experimental characterization (AE-SRM). The spatial response of the system, obtained by using the two approaches, was compared with experimental data. The effect of the MC-SRM and AE-SRM approaches on the reconstructed image was assessed in terms of image contrast, signal-to-noise ratio, image quality, and spatial resolution. To this end, acquisitions were carried out using a hot cylinder phantom (consisting of five fillable rods with diameters of 5, 4, 3, 2, and 1 mm and a uniform cylindrical chamber) and a custom-made Derenzo phantom, with center-to-center distances between adjacent rods of 1.5, 2.0, and 3.0 mm. RESULTS: Good agreement was found for the spatial response of the system between measured data and results derived from MC-SRM and AE-SRM. Only minor differences for point sources at distances smaller than the radius of rotation and large incidence angles were found. Assessment of the effect on the reconstructed image showed a similar contrast for both approaches, with values higher than 0.9 for rod diameters greater than 1 mm and higher than 0.8 for rod diameter of 1 mm. The comparison in terms of image quality showed that all rods in the different sections of a custom-made Derenzo phantom could be distinguished. The spatial resolution (FWHM) was 0.7 mm at iteration 100 using both approaches. The SNR was lower for reconstructed images using MC-SRM than for those reconstructed using AE-SRM, indicating that AE-SRM deals better with the projection noise than MC-SRM. CONCLUSIONS: The authors' findings show that both approaches provide good solutions to the problem of calculating the SRM in pinhole SPECT reconstruction. The AE-SRM was faster to create and handle the projection noise better than MC-SRM. Nevertheless, the AE-SRM required a tedious experimental characterization of the intrinsic detector response. Creation of the MC-SRM required longer computation time and handled the projection noise worse than the AE-SRM.Nevertheless, the MC-SRM inherently incorporates extensive modeling of the system and therefore experimental characterization was not required

Analytical, experimental, and Monte Carlo system response matrix for pinhole SPECT reconstruction

Purpose: To assess the performance of two approaches to the system response matrix (SRM) calculation in pinhole single photon emission computed tomography (SPECT) reconstruction. Methods: Evaluation was performed using experimental data from a low magnification pinhole SPECT system that consisted of a rotating flat detector with a monolithic scintillator crystal. The SRM was computed following two approaches, which were based on Monte Carlo simulations (MC-SRM) and analytical techniques in combination with an experimental characterization (AE-SRM). The spatial response of the system, obtained by using the two approaches, was compared with experimental data. The effect of the MC-SRM and AE-SRM approaches on the reconstructed image was assessed in terms of image contrast, signal-to-noise ratio, image quality, and spatial resolution. To this end, acquisitions were carried out using a hot cylinder phantom (consisting of five fillable rods with diameters of 5, 4, 3, 2, and 1 mm and a uniform cylindrical chamber) and a custom-made Derenzo phantom, with center-to-center distances between adjacent rods of 1.5, 2.0, and 3.0 mm. Results: Good agreement was found for the spatial response of the system between measured data and results derived from MC-SRM and AE-SRM. Only minor differences for point sources at distances smaller than the radius of rotation and large incidence angles were found. Assessment of the effect on the reconstructed image showed a similar contrast for both approaches, with values higher than 0.9 for rod diameters greater than 1 mm and higher than 0.8 for rod diameter of 1 mm. The comparison in terms of image quality showed that all rods in the different sections of a custom-made Derenzo phantom could be distinguished. The spatial resolution (FWHM) was 0.7 mm at iteration 100 using both approaches. The SNR was lower for reconstructed images using MC-SRM than for those reconstructed using AE-SRM, indicating that AE-SRM deals better with the projection noise than MC-SRM. Conclusions: The authors' findings show that both approaches provide good solutions to the problem of calculating the SRM in pinhole SPECT reconstruction. The AE-SRM was faster to create and handle the projection noise better than MC-SRM. Nevertheless, the AE-SRM required a tedious experimental characterization of the intrinsic detector response. Creation of the MC-SRM required longer computation time and handled the projection noise worse than the AE-SRM.Nevertheless, the MC-SRM inherently incorporates extensive modeling of the system and therefore experimental characterization was not required

Combined Neutron Imaging and Diffraction: Instrumentation and Experimentation

A combined neutron imaging and diffraction facility, IMAT (Imaging and Materials Science & Engineering) is developed at ISIS (Target Station 2). One subject of this thesis was focused on the design and optimization of the imaging part of IMAT, using the Monte Carlo calculation software package McStas. Hence, the neutron guide dimensions, the effects of the gaps in the neutron guide on imaging detectors, gravitation effects in the neutron guide and also the influence of the pinhole size on the image were studied. All these investigations were made taking into account the most important design criteria: to maximise the neutron flux, to obtain a good energy resolution whilst retaining a large neutron bandwidth and a long flight path and to minimize the artefacts obtained in the neutron radiographies. After a compromise between imaging, diffraction and engineering requirements had been reached, the results from simulations specific to the current IMAT design were studied: wavelength distribution, beam profiles at different points along the beamline, beam divergence, neutron intensity distribution and flux depending on the pinhole size and the wavelength bands. Moreover, generation of IMAT imaging data with a sample led to full tomographic simulations and modelling wavelength effects. Another objective of the thesis was to study the complementarity between neutron imaging and neutron diffraction experiments. For this, a new instrument control concept that exploits tomography data to guide diffraction experiments on samples with complex structures and shapes named “tomography driven diffraction” (henceforth, TDD) was developed. The method has been proved to be viable using combinations of individual tomography and diffraction instruments: NEUTRA (PSI) and ENGIN-X (ISIS) for different samples drawn from the engineering and heritage sciences. On IMAT it will be possible to perform tomography, mark the measurement points and proceed to the diffraction measurements as one continuous process

Targeted optimization of chromatographic columns based on 3D analysis of packing microstructure

The preparation, structure, and performance of functional materials porous are strongly interrelated. Hence, a detailed analysis of the pore structure of a functional porous material in combination with a detailed characterisation of its performance can provide an understanding of the influence of individual parameters during preparation and thus identify structural limitations to an improved utilization. The obtained results can be used to tune the preparation towards a better pore structure suited for the targeted application. This work focuses on packings of silica-based particles for highly efficient chromatographic separations. The prepared packings combine an interparticle macropore space for fast flow-based transport with an intraparticle mesopore space providing high surface areas for molecule-surface interactions. Such packed columns have a wide field of application, not only in highly efficient separations, but also for catalysis, and (energy) storage However, the focus here is on separations in liquid chromatography. In Chapter 1, the influence of the slurry concentration on separation efficiency and bed structure was investigated for capillary columns (75 µm inner diameter, 30 cm length) packed with 1.3 µm bridged-ethyl hybrid (BEH) fully porous silica particles. The slurry concentration was varied from 5 to 50 mg/mL while every other packing parameter was kept constant. Chromatographic characterisation with hydroquinone as weakly retained analyte revealed highly efficient separations (reduced plate heights as low as 1.5) at an optimal intermediate slurry concentration of 20 mg/mL for this specific set of packing parameters. Confocal laser scanning microscopy (CLSM) was utilized to conduct a three-dimensional reconstruction and to carry out a detailed morphological analysis of the column with the best performance, a column packed with a slurry concentration below the optimum, and one packed above the optimum. Two counteracting effects were revealed: Radial heterogeneities limit the separation efficiency for columns packed at low slurry concentrations. With an increase in slurry concentration, these radial effects get supressed but the number and size of large voids with a diameter similar to the mean particle diameter increase significantly. Interestingly, the reconstructions also revealed high external bed porosities between 0.47 and 0.50 which are higher than expected with respect to the random loose packing limit reported for frictional, cohesionless particles. However, no signs of bed instability could be observed demonstrating the significant impact of interparticle forces for particles as small as 1.3 µm. In Chapter 2, the investigation of the optimal slurry concentration was expanded by analysing the effects for a different particle size to obtain a more general picture. A similar set of capillary columns (75 µm inner diameter, 45 cm length) was packed with 1.9 µm BEH particles at eleven different slurry concentrations between 5 and 200 mg/mL including additional tests for reproducibility at selected concentrations and the observation of bed formation using optical microscopy. While comparable reduced plate heights were achieved, the observed optimum of 140-160 mg/mL to pack highly efficient columns reproducibly differed significantly from the 20 mg/mL for the 1.3 µm particles identified in Chapter 1. This can be explained by the difference in the particle diameter as interparticle forces and particle aggregation become more dominant at still smaller diameters. CLSM-based reconstructions revealed similar trends in the bed structures as seen in Chapter 1. At low concentrations, pronounced ordered particle layers in the direct vicinity of the column wall, local bed densification near the column wall, and particle size-segregation limit the achieved separation efficiency. The peculiarity of the first effect is continuously decreasing with an increase in the slurry concentration even beyond the optimum while the latter two effects are already supressed at the optimal slurry concentration. On the other hand, the number and size of large voids increase with an increase in the utilized slurry concentration as already seen in Chapter 1. The videos acquired during column packing provided very helpful insights into bed formation mechanisms and thus delivered possible explanations for these structural features. At 10 mg/mL, particles arrive individually at the bed front allowing individual settlement and rearrangement on the arrival of following particles what allows a discrimination of particles according to their individual properties. The picture looks completely different for 100 mg/mL as example for higher concentrated slurries. Here, particles tend to aggregate during packing and arrive in large batches. This prevents discrimination of individual particles but significantly reduces the chances for rearrangement and is thus prone to the conservation of defects formed between the border of the arriving batches of particles and the front of the bed. Chapter 3 is based on the results obtained during the work presented in Chapters 1 and 2. The combination of high slurry concentration and ultrasound was already proposed there as chance to keep transcolumn heterogeneities as low as possible while preventing the formation of large voids. To test this hypothesis, two sets, each consisting of three capillary columns (75 µm inner diameter, 100 cm length) were packed with 1.9 µm BEH particles at a slurry concentration of 200 mg/mL; one set under application of ultrasound during packing, the other one without. All three columns, which underwent sonication, showed significantly better performance than each of the other columns. The obtained reduced minimum plate height for a weakly retained analyte was even lower than the already impressive value of 1.5 for columns packed at a slurry concentration optimal for packing without sonication and reached values close to unity over a length of 1 m for the best-performing column. The achieved theoretical plate counts of ~500,000 demonstrate a unique potential for highly efficient separations of extremely complex samples. In Chapter 4, the focus is shifted from capillary columns to the more common analytical format. CLSM could not be applied here as the steel columns are not transparent and extrusion of the bed is not possible without losing either stability or optical transparency. Thus, an imaging and reconstruction procedure based on focused ion beam scanning electron microscopy was developed using a commercial narrow-bore analytical column (2.1 mm inner diameter, 50 mm length) packed with 1.7 µm BEH particles. The packing was embedded with poly(divinylbenzene) prior to extrusion from the steel column in order to conserve the bed structure. Two image stacks were acquired and reconstructed at characteristic positions within the bed: one in the central section of the column along the flow direction to obtain the bulk properties of the bed and one from the column wall towards the column centre to investigate and quantify the influence of the geometrical wall effect and the second wall effect. To investigate the effect of the microstructure in the wall region on local flow through the bed, a radially resolved flow profile was obtained by lattice-Boltzmann simulations. For this column, the region affected by wall effects spanned over approximately 62 particle diameters showing a decrease in the local mean porosity by up to 10% and an increase in the local mean particle diameter by up to 3% with respect to the bulk region inducing a decrease of the local flow velocity by up to 23%. Furthermore, four more ordered layers of particles were formed directly at the hard column wall due to the geometrical wall effect leading to local velocity fluctuations by up to a factor of three. These quantified structural features are in excellent agreement with previous reports about macroscopic characterisations of the wall effects by optical or chromatographic measurements

Computational Depth-resolved Imaging and Metrology

In this thesis, the main research challenge boils down to extracting 3D spatial information of an object from 2D measurements using light. Our goal is to achieve depth-resolved tomographic imaging of transparent or semi-transparent 3D objects, and to perform topography characterization of rough surfaces. The essential tool we used is computational imaging, where depending on the experimental scheme, often indirect measurements are taken, and tailored algorithms are employed to perform image reconstructions. The computational imaging approach enables us to relax the hardware requirement of an imaging system, which is essential when using light in the EUV and x-ray regimes, where high-quality optics are not readily available. In this thesis, visible and infrared light sources are used, where computational imaging also offers several advantages. First of all, it often leads to a simple, flexible imaging system with low cost. In the case of a lensless configuration, where no lenses are involved in the final image-forming stage between the object and the detector, aberration-free image reconstructions can be obtained. More importantly, computational imaging provides quantitative reconstructions of scalar electric fields, enabling phase imaging, numerical refocus, as well as 3D imaging

Computer vision and optimization methods applied to the measurements of in-plane deformations

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