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NASA NTRS1992

Active figure maintenance control using an optical truss laser metrology system for a space-based far-IR segmented telescope

A two-stage active control approach was developed addressing the figure control problem for a spaceborne FIR telescope, the Precision Segmented Reflectors Focus Moderate Mission Telescope (FMMT). The first active control stage aligns the optical segments based on images; attention is here given to the second stage, active figure maintenance control system, which maintains the alignment of the optical elements between initializations to hold the mirror figure steady while obtaining data and fixes translational and rotational changes of the optical segments induced by long-term thermal drifts of the support structure. Errors are expected to be 10-100 microns at the nodes of the primary backup structure over the course of an orbit. An rms performance of 0.8 microns of wavefront error can be expected during the maintenance function based on specified nominal sensor noises, actuator accuracies, and system environments. A performance of less than 0.3 microns rms can be expected, based on advanced components.

Lau, Kenneth↗

DOE OSTI2017

AN INDUCTIVE MAPPING WITH CONVOLUTIONAL REPRESENTATIONS FOR HUMAN SETTLEMENT DETECTION: PRELIMINARY RESULTS

Undoubtedly, deep convolutional learning methods continue to improve performance in image-level classification for computer vision and remote sensing applications. However, the spatio-temporal nature of remote sensing imagery offers other interesting challenges in multiscale image understanding. Emerging opportunities include seeking fine-grained and neighborhood mapping with overhead imagery. Limitations due to lack of relevant scale ground-truth often mandates that these challenges are pursued as disjoint. We test this premise and explore representation spaces from a single deep convolutional network and their visualization to argue for a unified feature extraction framework. The objective is to utilize and re-purpose trained feature extractors without the need for network retraining on three remote sensing tasks i.e. superpixel mapping, pixel-level segmentation and semantic based image visualization. By leveraging the same convolutional feature extractors and viewing them as visual information extractors that encode different image representation spaces, we demonstrate surprising potential on multiscale experiments that incorporate edge-level details up to semantic-level informationWe test this premise and explore representation spaces from a single deep convolutional network and their visualization to argue for a novel unified feature extraction framework. The objective is to utilize and re-purpose trained feature extractors without the need for network retraining on three remote sensing tasks i.e. superpixel mapping, pixel-level segmentation and semantic based image visualization. By leveraging the same convolutional feature extractors and viewing them as visual information extractors that encode different image representation spaces, we demonstrate a preliminary inductive transfer learning potential on multiscale experiments that incorporate edge-level details up to semantic-level informationWe test this premise and explore representation spaces from a single deep convolutional network and their visualization to argue for a novel unified feature extraction framework. The objective is to utilize and re-purpose trained feature extractors without the need for network retraining on three remote sensing tasks i.e. superpixel mapping, pixel-level segmentation and semantic based image visualization. By leveraging the same convolutional feature extractors and viewing them as visual information extractors that encode different image representation spaces, we demonstrate a preliminary inductive transfer learning potential on multiscale experiments that incorporate edge-level details up to semantic-level information.

Lunga, Dalton↗

DOE OSTI2012

A Bayesian nonrigid registration method to enhance intraoperative target definition in image-guided prostate procedures through uncertainty characterization

Purpose: This study introduces a probabilistic nonrigid registration method for use in image-guided prostate brachytherapy. Intraoperative imaging for prostate procedures, usually transrectal ultrasound (TRUS), is typically inferior to diagnostic-quality imaging of the pelvis such as endorectal magnetic resonance imaging (MRI). MR images contain superior detail of the prostate boundaries and provide substructure features not otherwise visible. Previous efforts to register diagnostic prostate images with the intraoperative coordinate system have been deterministic and did not offer a measure of the registration uncertainty. The authors developed a Bayesian registration method to estimate the posterior distribution on deformations and provide a case-specific measure of the associated registration uncertainty. Methods: The authors adapted a biomechanical-based probabilistic nonrigid method to register diagnostic to intraoperative images by aligning a physician's segmentations of the prostate in the two images. The posterior distribution was characterized with a Markov Chain Monte Carlo method; the maximum a posteriori deformation and the associated uncertainty were estimated from the collection of deformation samples drawn from the posterior distribution. The authors validated the registration method using a dataset created from ten patients with MRI-guided prostate biopsies who had both diagnostic and intraprocedural 3 Tesla MRI scans. The accuracy and precision of the estimated posterior distribution on deformations were evaluated from two predictive distance distributions: between the deformed central zone-peripheral zone (CZ-PZ) interface and the physician-labeled interface, and based on physician-defined landmarks. Geometric margins on the registration of the prostate's peripheral zone were determined from the posterior predictive distance to the CZ-PZ interface separately for the base, mid-gland, and apical regions of the prostate. Results: The authors observed variation in the shape and volume of the segmented prostate in diagnostic and intraprocedural images. The probabilistic method allowed us to convey registration results in terms of posterior distributions, with the dispersion providing a patient-specific estimate of the registration uncertainty. The median of the predictive distance distribution between the deformed prostate boundary and the segmented boundary was Less-Than-Or-Slanted-Equal-To 3 mm (95th percentiles within {+-}4 mm) for all ten patients. The accuracy and precision of the internal deformation was evaluated by comparing the posterior predictive distance distribution for the CZ-PZ interface for each patient, with the median distance ranging from -0.6 to 2.4 mm. Posterior predictive distances between naturally occurring landmarks showed registration errors of Less-Than-Or-Slanted-Equal-To 5 mm in any direction. The uncertainty was not a global measure, but instead was local and varied throughout the registration region. Registration uncertainties were largest in the apical region of the prostate. Conclusions: Using a Bayesian nonrigid registration method, the authors determined the posterior distribution on deformations between diagnostic and intraprocedural MR images and quantified the uncertainty in the registration results. The feasibility of this approach was tested and results were positive. The probabilistic framework allows us to evaluate both patient-specific and location-specific estimates of the uncertainty in the registration result. Although the framework was tested on MR-guided procedures, the preliminary results suggest that it may be applied to TRUS-guided procedures as well, where the addition of diagnostic MR information may have a larger impact on target definition and clinical guidance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Particle tracking during Ostwald ripening using time-resolved laboratory X-ray microtomography

Laboratory X-ray microtomography is investigated as a method for obtaining time-resolved images of microstructural coarsening of the semisolid state of Al–5 wt.% Cu samples during Ostwald ripening. Owing to the 3D imaging capability of tomography, this technique uniquely provides access to the growth rates of individual particles, thereby not only allowing a statistical characterization of coarsening—as has long been possible by conventional metallography—but also enabling quantification of the influence of local environment on particle boundary migration. The latter information is crucial to understanding growth kinetics during Ostwald ripening at high volume fractions of the coarsening phase. Automated image processing and segmentation routines were developed to close gaps in the network of particle boundaries and to track individual particles from one annealing step to the next. The particle tracking success rate places an upper bound of only a few percent on the likelihood of segmentation errors for any given particle. The accuracy of particle size trajectories extracted from the time-resolved tomographic reconstructions is correspondingly high. Statistically averaged coarsening data and individual particle growth rates are in excellent agreement with the results of prior experimental studies and with computer simulations of Ostwald ripening. - Highlights: • Ostwald ripening in Al–5 wt.% Cu measured by laboratory X-ray microtomography • Time-resolved measurement of individual particle growth • Automated segmentation routines developed to close gaps in particle boundary network • Particle growth/shrinkage rates deviate from LSW model prediction.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Simulation-trained machine learning models for Lorentz transmission electron microscopy

Understanding the collective behavior of complex spin textures, such as lattices of magnetic skyrmions, is of fundamental importance for exploring and controlling the emergent ordering of these spin textures and inducing phase transitions. It is also critical to understand the skyrmion–skyrmion interactions for applications such as magnetic skyrmion-enabled reservoir or neuromorphic computing. Magnetic skyrmion lattices can be studied using in situ Lorentz transmission electron microscopy (LTEM), but quantitative and statistically robust analysis of the skyrmion lattices from LTEM images can be difficult. In this work, we show that a convolutional neural network, trained on simulated data, can be applied to perform segmentation of spin textures and to extract quantitative data, such as spin texture size and location, from experimental LTEM images, which cannot be obtained manually. This includes quantitative information about skyrmion size, position, and shape, which can, in turn, be used to calculate skyrmion–skyrmion interactions and lattice ordering. We apply this approach to segmenting images of Néel skyrmion lattices so that we can accurately identify skyrmion size and deformation in both dense and sparse lattices. The model is trained using a large set of micromagnetic simulations as well as simulated LTEM images. This entirely open-source training pipeline can be applied to a wide variety of magnetic features and materials, enabling large-scale statistical studies of spin textures using LTEM.

McCray, Arthur R. C. (ORCID:0000000160774698)↗

NASA NTRS1994

Non-subjective cataract analysis and its application in space radiation risk assessment

Experimental animal studies and human observations suggest that the question is not whether or not prolonged space missions will cause cataracts to appear prematurely in the astronauts, but when and to what degree. Historically the major impediment to radiation cataract follow-up has been the necessarily subjective nature of assessing the degree of lens transparency. This has spurred the development of instruments which produce video images amenable to digital analysis. One such system, the Zeiss Scheimpflug slit lamp measuring system (SLC), was incorporated into our ongoing studies of radiation cataractogenesis. It was found that the Zeiss SLC measuring system has high resolution and permits the acquisition of reproducible images of the anterior segment of the eye. Our results, based on about 650 images of the rats lens, and followed over a period of 91 weeks of radiation cataract development, showed that the Integrated Optical Density (IOD) of the lens correlated well with conventional assessment with the added advantages of objectivity, permanent and transportable records and linearity as cataracts become more severe. This continuous data acquisition, commencing with cataract onset, can proceed through more advanced stages. The SLC exhibits much greater sensitivity reflected in a continuously progressive severity despite the artifactual plateaus in staging which occur using conventional scoring methods. Systems such as the Zeiss SLC should be used to monitor astronauts frequent visits to low earth orbit to obtain a longitudinal data-base on the influence of this activity on the lens.

Wu, B.↗

NASA NTRS1995

Use of non-subjective analysis of lens transparency in experimental radiation cataract research

Historically the major impediment to radiation cataract follow-up has been the necessarily subjective nature of assessing the degree of lens transparency. This has spurred the development of instruments which produce video images amenable to digital analysis. One such system, the Zeiss Scheimpflug slit lamp measuring system (SLC), was incorporated into our ongoing studies of radiation cataractogenesis. It was found that the Zeiss SLC measuring system has high resolution and permits the acquisition of reproducible images of the anterior segment of the eye. Our results, based on about 650 images of lenses followed over a period of 91 weeks of radiation cataract development, showed that the changes in the light scatter of the lens correlated well with conventional assessment of radiation cataracts with the added advantages of objectivity, permanent and transportable records and linearity as cataracts become more severe. This continuous data acquisition, commencing with cataract onset, can proceed through more advanced stages. The SLC exhibits much greater sensitivity reflected in a continuously progressive severity thereby avoiding the artifactual plateaus in staging which occur using conventional scoring methods.

NASA Discipline Number 04-10↗

DOE OSTI2023

Supporting information for Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

In this work, we use few-shot learning to segment the body and vein architecture of P. trichocarpa leaves from high-resolution scans obtained in the UC Davis common garden. Leaf and vein segmentation are formulated as separate tasks, in which convolutional neural networks (CNNs) are used to iteratively expand partial segmentations until reaching stopping criteria. Our leaf and vein segmentation approaches use just 50 and 8 manually traced images for training, respectively, and are applied to a set of 2,634 top and bottom leaf scans. We show that both methods achieve high segmentation accuracy, in some cases exceeding even human-level segmentation. The leaf and vein segmentations are subsequently used to extract 68 morphological traits using traditional open-source image processing tools, which are validated using real-world physical measurements. For a biological perspective, we perform a genome-wide association study using the vein density trait to discover novel genetic architectures associated with multiple physiological processes relating to leaf development and function. In addition to sharing all of the few-shot learning code (see https://github.com/jlager/few-shot-leaf-segmentation), we are releasing all images, manual segmentations, model predictions, 68 extracted leaf phenotypes, and a new set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes. The data folder includes all images, ground truth segmentations, predicted segmentations, and extracted leaf traits. All images encode the sample ID in the file name by indicating the treatment, block, row, position, and leaf side, respectively. For example, the file, C_1_1_2_bot.jpeg, indicates the control treatment, block 1, row 1, position 2, and the bottom side of the leaf. Tabulated results include position IDs as well as the corresponding genotype IDs. The images folder includes the 2,906 high-resolution leaf scans taken in the field. The leaf_masks folder includes 50 ground truth segmentations used for training the leaf tracing algorithm. The leaf_preds folder includes the 2,906 predicted segmentations from the leaf tracing algorithm. The vein_masks folder includes 8 ground truth segmentations used for training the vein growing algorithm. The vein_preds folder includes the 1,453 predicted segmentations from the vein growing algorithm. The vein_probs folder includes the 1,453 predicted probability maps from the vein growing algorithm before thresholding. The genomes folder includes the set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes with a README file detailing the steps taken. The results folder includes: (i) raw values of the 68 predicted leaf traits in digital_traits.tsv, (ii) manually measured values of petiole length and width in manual_traits.tsv, (iii) thin plate spline (TPS) adjusted values of the vein density trait in vein_density_tps_adj.tsv, (iv) best linear unbiased prediction (BLUP) adjusted values of the vein density trait in vein_density_blups.tsv, and (v) GWAS results for the vein density trait, including chromosome positions and corresponding P values, in gwas_results.csv.

09 BIOMASS FUELS↗

NASA NTRS1992

Clustering methods for removing outliers from vision-based range estimates

The present approach to the automation of helicopter low-altitude flight uses one or more passive imaging sensors to extract environmental obstacle information; this is then processed via computer-vision techniques to yield a time-varying map of range to obstacles in the sensor's field of view along the vehicle's flight path. Attention is given to two related techniques which can eliminate outliers from a sparse range map, clustering sparse range-map information into different spatial classes that rely on a segmented and labeled image to aid in spatial classification within the image plane.

Hussien, B.↗

DOE OSTI2014

Optimization of the design of thick, segmented scintillators for megavoltage cone-beam CT using a novel, hybrid modeling technique

Purpose: Active matrix flat-panel imagers (AMFPIs) incorporating thick, segmented scintillators have demonstrated order-of-magnitude improvements in detective quantum efficiency (DQE) at radiotherapy energies compared to systems based on conventional phosphor screens. Such improved DQE values facilitate megavoltage cone-beam CT (MV CBCT) imaging at clinically practical doses. However, the MV CBCT performance of such AMFPIs is highly dependent on the design parameters of the scintillators. In this paper, optimization of the design of segmented scintillators was explored using a hybrid modeling technique which encompasses both radiation and optical effects. Methods: Imaging performance in terms of the contrast-to-noise ratio (CNR) and spatial resolution of various hypothetical scintillator designs was examined through a hybrid technique involving Monte Carlo simulation of radiation transport in combination with simulation of optical gain distributions and optical point spread functions. The optical simulations employed optical parameters extracted from a best fit to measurement results reported in a previous investigation of a 1.13 cm thick, 1016μm pitch prototype BGO segmented scintillator. All hypothetical designs employed BGO material with a thickness and element-to-element pitch ranging from 0.5 to 6 cm and from 0.508 to 1.524 mm, respectively. In the CNR study, for each design, full tomographic scans of a contrast phantom incorporating various soft-tissue inserts were simulated at a total dose of 4 cGy. Results: Theoretical values for contrast, noise, and CNR were found to be in close agreement with empirical results from the BGO prototype, strongly supporting the validity of the modeling technique. CNR and spatial resolution for the various scintillator designs demonstrate complex behavior as scintillator thickness and element pitch are varied—with a clear trade-off between these two imaging metrics up to a thickness of ∼3 cm. Based on these results, an optimization map indicating the regions of design that provide a balance between these metrics was obtained. The map shows that, for a given set of optical parameters, scintillator thickness and pixel pitch can be judiciously chosen to maximize performance without resorting to thicker, more costly scintillators. Conclusions: Modeling radiation and optical effects in thick, segmented scintillators through use of a hybrid technique can provide a practical way to gain insight as to how to optimize the performance of such devices in radiotherapy imaging. Assisted by such modeling, the development of practical designs should greatly facilitate low-dose, soft tissue visualization employing MV CBCT imaging in external beam radiotherapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2018

Combined Static and Dynamic Computed Tomography Angiography of Peripheral Artery Occlusive Disease: Comparison with Magnetic Resonance Angiography

PurposeTo compare in patients with known peripheral artery occlusive disease (PAOD), image quality of a combined CTA to a combined MRA protocol, including both static and dynamic acquisitions.Materials and MethodsTwenty-two patients with PAOD were examined with a combined CTA and MRA protocol consisting of static acquisitions (s-CTA, s-MRA) of the entire runoff and dynamic acquisitions (d-CTA, d-MRA) of the calves. Two radiologists compared image quality of the s-MRA versus s-CTA as well as d-MRA versus d-CTA. Image quality was assessed on a segmental basis using a 4-point Likert scale.ResultsFor s-CTA, 76% of segments were rated as excellent or good. For s-MRA, 50% of segments were rated as excellent or good (p < 0.0001). For d-CTA, median image quality score for all segments was rated as excellent for both readers. For d-MRA, median image quality for the different segments ranged from moderate to good. For both d-CTA and d-MRA, the median image quality scores were significantly higher for all segments of the lower limb compared with the static examinations of the lower limb segments (all p values < 0.0001). In patients with PAOD category 4–6, 80% of segments were rated as excellent or good for d-CTA, while 45% of segments were rated as poor or non-diagnostic for d-MRA.ConclusionIn patients with known PAOD, a combined static and dynamic CTA examination improves image quality relative to static and dynamic MRA and should be considered as an alternative to MRA, particularly in patients with advanced stage PAOD.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRS2010

Sparse Superpixel Unmixing for Hyperspectral Image Analysis

Software was developed that automatically detects minerals that are present in each pixel of a hyperspectral image. An algorithm based on sparse spectral unmixing with Bayesian Positive Source Separation is used to produce mineral abundance maps from hyperspectral images. A superpixel segmentation strategy enables efficient unmixing in an interactive session. The algorithm computes statistically likely combinations of constituents based on a set of possible constituent minerals whose abundances are uncertain. A library of source spectra from laboratory experiments or previous remote observations is used. A superpixel segmentation strategy improves analysis time by orders of magnitude, permitting incorporation into an interactive user session (see figure). Mineralogical search strategies can be categorized as supervised or unsupervised. Supervised methods use a detection function, developed on previous data by hand or statistical techniques, to identify one or more specific target signals. Purely unsupervised results are not always physically meaningful, and may ignore subtle or localized mineralogy since they aim to minimize reconstruction error over the entire image. This algorithm offers advantages of both methods, providing meaningful physical interpretations and sensitivity to subtle or unexpected minerals.

Castano, Rebecca↗

NASA NTRS2012

Advances in Spectral-Spatial Classification of Hyperspectral Images

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

Fauvel, Mathieu↗

NASA NTRS2012

Advances in Spectral-Spatial Classification of Hyperspectral Images

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation, and contrast of the spatial structures present in the image. Then, the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines (SVMs) using the available spectral information and the extracted spatial information. Spatial postprocessing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple-classifier (MC) system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral–spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

hyperspectral image↗

DOE OSTI2015

X-ray computed tomography of wood-adhesive bondlines: Attenuation and phase-contrast effects

Microscale X-ray computed tomography (XCT) is discussed as a technique for identifying 3D adhesive distribution in wood-adhesive bondlines. Visualization and material segmentation of the adhesives from the surrounding cellular structures require sufficient gray-scale contrast in the reconstructed XCT data. Commercial wood-adhesive polymers have similar chemical characteristics and density to wood cell wall polymers and therefore do not provide good XCT attenuation contrast in their native form. Here, three different adhesive types, namely phenol formaldehyde, polymeric diphenylmethane diisocyanate, and a hybrid polyvinyl acetate, are tagged with iodine such that they yield sufficient X-ray attenuation contrast. However, phase-contrast effects at material edges complicate image quality and segmentation in XCT data reconstructed with conventional filtered backprojection absorption contrast algorithms. A quantitative phase retrieval algorithm, which isolates and removes the phase-contrast effect, was demonstrated. The paper discusses and illustrates the balance between material X-ray attenuation and phase-contrast effects in all quantitative XCT analyses of wood-adhesive bondlines.

36 MATERIALS SCIENCE↗

NASA NTRS2002

Contrast and harmonic imaging improves accuracy and efficiency of novice readers for dobutamine stress echocardiography

BACKGROUND: Newer contrast agents as well as tissue harmonic imaging enhance left ventricular (LV) endocardial border delineation, and therefore, improve LV wall-motion analysis. Interpretation of dobutamine stress echocardiography is observer-dependent and requires experience. This study was performed to evaluate whether these new imaging modalities would improve endocardial visualization and enhance accuracy and efficiency of the inexperienced reader interpreting dobutamine stress echocardiography. METHODS AND RESULTS: Twenty-nine consecutive patients with known or suspected coronary artery disease underwent dobutamine stress echocardiography. Both fundamental (2.5 MHZ) and harmonic (1.7 and 3.5 MHZ) mode images were obtained in four standard views at rest and at peak stress during a standard dobutamine infusion stress protocol. Following the noncontrast images, Optison was administered intravenously in bolus (0.5-3.0 ml), and fundamental and harmonic images were obtained. The dobutamine echocardiography studies were reviewed by one experienced and one inexperienced echocardiographer. LV segments were graded for image quality and function. Time for interpretation also was recorded. Contrast with harmonic imaging improved the diagnostic concordance of the novice reader to the expert reader by 7.1%, 7.5%, and 12.6% (P < 0.001) as compared with harmonic imaging, fundamental imaging, and fundamental imaging with contrast, respectively. For the novice reader, reading time was reduced by 47%, 55%, and 58% (P < 0.005) as compared with the time needed for fundamental, fundamental contrast, and harmonic modes, respectively. With harmonic imaging, the image quality score was 4.6% higher (P < 0.001) than for fundamental imaging. Image quality scores were not significantly different for noncontrast and contrast images. CONCLUSION: Harmonic imaging with contrast significantly improves the accuracy and efficiency of the novice dobutamine stress echocardiography reader. The use of harmonic imaging reduces the frequency of nondiagnostic wall segments.

Non-NASA Center↗

NASA NTRS1995

Full resolution hologram-like autostereoscopic display

Under this program, Dimension Technologies Inc. (DTI) developed a prototype display that uses a proprietary illumination technique to create autostereoscopic hologram-like full resolution images on an LCD operating at 180 fps. The resulting 3D image possesses a resolution equal to that of the LCD along with properties normally associated with holograms, including change of perspective with observer position and lack of viewing position restrictions. Furthermore, this autostereoscopic technique eliminates the need to wear special glasses to achieve the parallax effect. Under the program a prototype display was developed which demonstrates the hologram-like full resolution concept. To implement such a system, DTI explored various concept designs and enabling technologies required to support those designs. Specifically required were: a parallax illumination system with sufficient brightness and control; an LCD with rapid address and pixel response; and an interface to an image generation system for creation of computer graphics. Of the possible parallax illumination system designs, we chose a design which utilizes an array of fluorescent lamps. This system creates six sets of illumination areas to be imaged behind an LCD. This controlled illumination array is interfaced to a lenticular lens assembly which images the light segments into thin vertical light lines to achieve the parallax effect. This light line formation is the foundation of DTI's autostereoscopic technique. The David Sarnoff Research Center (Sarnoff) was subcontracted to develop an LCD that would operate with a fast scan rate and pixel response. Sarnoff chose a surface mode cell technique and produced the world's first large area pi-cell active matrix TFT LCD. The device provided adequate performance to evaluate five different perspective stereo viewing zones. A Silicon Graphics' Iris Indigo system was used for image generation which allowed for static and dynamic multiple perspective image rendering. During the development of the prototype display, we identified many critical issues associated with implementing such a technology. Testing and evaluation enabled us to prove that this illumination technique provides autostereoscopic 3D multi perspective images with a wide range of view, smooth transition, and flickerless operation given suitable enabling technologies.

Eichenlaub, Jesse B.↗

DOE OSTI2013

A whole-system approach to x-ray spectroscopy in cargo inspection systems

The bremsstrahlung x-ray spectrum used in high-energy, high-intensity x-ray cargo inspection systems is attenuated and modified by the materials in the cargo in a Z-dependent way. Therefore, spectroscopy of the detected x rays yields information about the Z of the x-rayed cargo material. It has previously been shown that such ZSpectroscopy (Z-SPEC) is possible under certain circumstances. A statistical approach, Z-SCAN (Z-determination by Statistical Count-rate ANalysis), has also been shown to be effective, and it can be used either by itself or in conjunction with Z-SPEC when the x-ray count rate is too high for individual x-ray spectroscopy. Both techniques require fast x-ray detectors and fast digitization electronics. It is desirable (and possible) to combine all techniques, including x-ray imaging of the cargo, in a single detector array, to reduce costs, weight, and overall complexity. In this paper, we take a whole-system approach to x-ray spectroscopy in x-ray cargo inspection systems, and show how the various parts interact with one another. Faster detectors and read-out electronics are beneficial for both techniques. A higher duty-factor x-ray source allows lower instantaneous count rates at the same overall x-ray intensity, improving the range of applicability of Z-SPEC in particular. Using an intensity-modulated advanced x-ray source (IMAXS) allows reducing the x-ray count rate for cargoes with higher transmission, and a stacked-detector approach may help material discrimination for the lowest attenuations. Image processing and segmentation allow derivation of results for entire objects, and subtraction of backgrounds. We discuss R and D performed under a number of different programs, showing progress made in each of the interacting subsystems. We discuss results of studies into faster scintillation detectors, including ZnO, BaF{sub 2} and PbWO{sub 4}, as well as suitable photo-detectors, read-out and digitization electronics. We discuss high-duty-factor linear-accelerator x-ray sources and their associated requirements, and how such sources improve spectroscopic techniques. We further discuss how image processing techniques help in correcting for backgrounds and overlapping materials. In sum, we present an integrated picture of how to optimize a cargo inspection system for x-ray spectroscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗