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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Optical authentication of images

Systems and methods performed for generating authentication information for an image using optical computing are provided. When a user takes a photo of an object, an optical authentication system receives light reflected and/or emitted from the object. The system also receives a random key from an authentication server. The system converts the received light to plenoptic data and uploads it to the authentication server. In addition, the system generates an optical hash of the received light using the random key, converts the generated optical hash to a digital optical hash, and uploads the digital optical hash to the authentication server. When the authentication server receives the upload, it verifies whether the time of the upload is within a certain threshold time from the sending of the random key and whether the digital optical hash was generated from the same light as the plenoptic data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Optical authentication of images

Systems and methods performed for generating authentication information for an image using optical computing are provided. When a user takes a photo of an object, an optical authentication system receives light reflected and/or emitted from the object. The system also receives a random key from an authentication server. The system converts the received light to plenoptic data and uploads it to the authentication server. In addition, the system generates an optical hash of the received light using the random key, converts the generated optical hash to a digital optical hash, and uploads the digital optical hash to the authentication server. When the authentication server receives the upload, it verifies whether the time of the upload is within a certain threshold time from the sending of the random key and whether the digital optical hash was generated from the same light as the plenoptic data.

Murialdo, Maxwell R.↗
DOE OSTI2014

Implications of CT noise and artifacts for quantitative {sup 99m}Tc SPECT/CT imaging

Purpose: This paper evaluates the effects of computed tomography (CT) image noise and artifacts on quantitative single-photon emission computed-tomography (SPECT) imaging, with the aim of establishing an appropriate range of CT acquisition parameters for low-dose protocols with respect to accurate SPECT attenuation correction (AC). Methods: SPECT images of two geometric and one anthropomorphic phantom were reconstructed iteratively using CT scans acquired at a range of dose levels (CTDI{sub vol} = 0.4 to 46 mGy). Resultant SPECT image quality was evaluated by comparing mean signal, background noise, and artifacts to SPECT images reconstructed using the highest dose CT for AC. Noise injection was performed on linear-attenuation (μ) maps to determine the CT noise threshold for accurate AC. Results: High levels of CT noise (σ ∼ 200–400 HU) resulted in low μ-maps noise (σ ∼ 1%–3%). Noise levels greater than ∼10% in 140 keV μ-maps were required to produce visibly perceptible increases of ∼15% in {sup 99m}Tc SPECT images. These noise levels would be achieved at low CT dose levels (CTDI{sub vol} = 4 μGy) that are over 2 orders of magnitude lower than the minimum dose for diagnostic CT scanners. CT noise could also lower (bias) the expected μ values. The relative error in reconstructed SPECT signal trended linearly with the relative shift in μ. SPECT signal was, on average, underestimated in regions corresponding with beam-hardening artifacts in CT images. Any process that has the potential to change the CT number of a region by ∼100 HU (e.g., misregistration between CT images and SPECT images due to motion, the presence of contrast in CT images) could introduce errors in μ{sub 140} {sub keV} on the order of 10%, that in turn, could introduce errors on the order of ∼10% into the reconstructed {sup 99m}Tc SPECT image. Conclusions: The impact of CT noise on SPECT noise was demonstrated to be negligible for clinically achievable CT parameters. Because CT dose levels that affect SPECT quantification is low (CTDI{sub vol} ∼ 4 μGy), the low dose limit for the CT exam as part of SPECT/CT will be guided by CT image quality requirements for anatomical localization and artifact reduction. A CT technique with higher kVp in combination with lower mAs is recommended when low-dose CT images are used for AC to minimize beam-hardening artifacts.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

TU-G-BRA-08: BEST IN PHYSICS (JOINT IMAGING-THERAPY): Hybrid PET-MRI Imaging of Acute Radiation Induced Cardiac Toxicity

Purpose: To identify the presence of low-dose radiation induced cardiac toxicity in a canine model using hybrid positron emission tomography (PET) and magnetic resonance imaging (MRI). Methods: Research ethics board approval was obtained for a longitudinal imaging study of 5 canines after cardiac irradiation. Animals were imaged at baseline, 1 week post cardiac irradiation, and 1 month post cardiac irradiation using a hybrid PET- MRI system (Biograph mMR, Siemens Healthcare). The imaging protocol was designed to assess acute changes in myocardial perfusion and inflammation. Myocardial perfusion imaging was performed using N13-ammonia tracer followed by a dynamic PET acquisition scan. A compartmental tracer kinetic model was used for absolute perfusion quantification. Myocardial inflammation imaging was performed using F18-fluorodeoxyglucose (FDG) tracer. The standard uptake value (SUV) over a region encompassing the whole heart was used to compare FDG scans. All animals received a simulation CT scan (GE Medical Systems) for radiation treatment planning. Radiation treatment plans were created using the Pinncale3 treatment planning system (Philips Radiation Oncology Systems) and designed to resemble the typical cardiac exposure during left-sided breast cancer radiotherapy. Cardiac irradiations were performed in a single fraction using a TrueBeam linear accelerator (Varian Medical Systems). Results: The delivered dose (mean ± standard deviation) to heart was 1.8±0.2 Gy. Reductions in myocardial stress perfusion relative to baseline were observed in 2 of the 5 animals 1 month post radiation. A global inflammatory response 1 month post radiation was observed in 4 of the 5 animals. The calculated SUV at 1 month post radiation was significantly higher (p=0.05) than the baseline SUV. Conclusion: Low doses of cardiac irradiation (< 2 Gy) may lead to myocardial perfusion defects and a global inflammatory response that can be detectable as early as 1 month post irradiation using hybrid PET-MRI imaging techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

System and method for magnetic current density imaging at ultra low magnetic fields

Preferred systems can include an electrical impedance tomography apparatus electrically connectable to an object; an ultra low field magnetic resonance imaging apparatus including a plurality of field directions and disposable about the object; a controller connected to the ultra low field magnetic resonance imaging apparatus and configured to implement a sequencing of one or more ultra low magnetic fields substantially along one or more of the plurality of field directions; and a display connected to the controller, and wherein the controller is further configured to reconstruct a displayable image of an electrical current density in the object. Preferred methods, apparatuses, and computer program products are also disclosed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Generic method for automatic bladder segmentation on cone beam CT using a patient-specific bladder shape model

Purpose: The aim of this study is to develop and validate a generic method for automatic bladder segmentation on cone beam computed tomography (CBCT), independent of gender and treatment position (prone or supine), using only pretreatment imaging data. Methods: Data of 20 patients, treated for tumors in the pelvic region with the entire bladder visible on CT and CBCT, were divided into four equally sized groups based on gender and treatment position. The full and empty bladder contour, that can be acquired with pretreatment CT imaging, were used to generate a patient-specific bladder shape model. This model was used to guide the segmentation process on CBCT. To obtain the bladder segmentation, the reference bladder contour was deformed iteratively by maximizing the cross-correlation between directional grey value gradients over the reference and CBCT bladder edge. To overcome incorrect segmentations caused by CBCT image artifacts, automatic adaptations were implemented. Moreover, locally incorrect segmentations could be adapted manually. After each adapted segmentation, the bladder shape model was expanded and new shape patterns were calculated for following segmentations. All available CBCTs were used to validate the segmentation algorithm. The bladder segmentations were validated by comparison with the manual delineations and the segmentation performance was quantified using the Dice similarity coefficient (DSC), surface distance error (SDE) and SD of contour-to-contour distances. Also, bladder volumes obtained by manual delineations and segmentations were compared using a Bland-Altman error analysis. Results: The mean DSC, mean SDE, and mean SD of contour-to-contour distances between segmentations and manual delineations were 0.87, 0.27 cm and 0.22 cm (female, prone), 0.85, 0.28 cm and 0.22 cm (female, supine), 0.89, 0.21 cm and 0.17 cm (male, supine) and 0.88, 0.23 cm and 0.17 cm (male, prone), respectively. Manual local adaptations improved the segmentation results significantly (p < 0.01) based on DSC (6.72%) and SD of contour-to-contour distances (0.08 cm) and decreased the 95% confidence intervals of the bladder volume differences. Moreover, expanding the shape model improved the segmentation results significantly (p < 0.01) based on DSC and SD of contour-to-contour distances. Conclusions: This patient-specific shape model based automatic bladder segmentation method on CBCT is accurate and generic. Our segmentation method only needs two pretreatment imaging data sets as prior knowledge, is independent of patient gender and patient treatment position and has the possibility to manually adapt the segmentation locally.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Imaging the inside of thick structures using cosmic rays

The authors present here a new method to image reinforcement elements inside thick structures and the results of a demonstration measurement performed on a mock-up wall built at Los Alamos National Laboratory. The method, referred to as “multiple scattering muon radiography”, relies on the use of cosmic-ray muons as probes. The work described in this article was performed to prove the viability of the technique as a means to image the interior of the dome of Florence Cathedral Santa Maria del Fiore, one of the UNESCO World Heritage sites and among the highest profile buildings in existence. Its result shows the effectiveness of the technique as a tool to radiograph thick structures and image denser object inside them.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2011

Methods for Radiometric Cross-Calibration of Imaging Sensors With and Without Overlapping Collections

This slide presentation reviews methods of cross calibration for imaging sensors. Cross calibration methods fall under two categories: (1) Relies on knowledge of a source that is common to both sensors, (2) Typically near-coincident views. Some work has used methods that do not require simultaneous data collections. This talk discusses the International System of Units (SI) -traceable approaches that permit cross-calibration. It describes on-orbit cross-calibration methods that are typically used, with and without overlapping views. It reviews sample results. It also describes a method without overlapping views and without on-site measurements.

Thome, K. J.↗
DOE OSTI2014

SU-E-I-72: First Experimental Study of On-Board CBCT Imaging Using 2.5MV Beam On a Radiotherapy Linac

Purpose: Varian TrueBeam version 2.0 comes with a new inline 2.5MV beam modality for image guided patient setup. In this work we develop an iterative volumetric image reconstruction technique specific to the beam and investigate the possibility of obtaining metal artifact free CBCT images using the new imaging modality. Methods: An iterative reconstruction algorithm with a sparse representation constraint based on dictionary learning is developed, in which both sparse projection and low dose rate (10 MU/min) are considered. Two CBCT experiments were conducted using the newly available 2.5MV beam on a Varian TrueBeam linac. First, a Rando anthropomorphic head phantom with and without a copper bar inserted in the center was scanned using both 2.5MV and kV (100kVp) beams. In a second experiment, an MRI phantom with many coils was scanned using 2.5MV, 6MV, and kV (100kVp) beams. Imaging dose and the resultant image quality is studied. Results: Qualitative assessment suggests that there were no visually detectable metal artifacts in MV CBCT images, compared with significant metal artifacts in kV CBCT images, especially in the MRI phantom. For a region near the metal object in the head phantom, the 2.5MV CBCT gave a more accurate quantification of the electron density compared with kV CBCT, with a ∼50% reduction in mean HU error. As expected, the contrast between bone and soft-tissue in 2.5MV CBCT decreased compared with kV CBCT. Conclusion: On-board CBCT imaging with the new 2.5MV beam can effectively reduce metal artifacts, although with a reduced softtissue contrast. Combination of kV and MV scanning may lead to metal artifact free CBCT images with uncompromised soft-tissue contrast.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-D-9A-04: Brain PET/CT Imaging On a Scanner with a Large Axial Field-Of-View

Purpose: Large axial field-of-view (FOV) PET/CT scanners are valued for high sensitivity. Brain PET image quality may depend on the head position within the FOV. We investigated the precision of activity estimation for brain PET imaging when the brain was positioned at the end (END) and in the middle (CEN) of the FOV. The additional CT dose for the CEN position was recorded. Methods: An image quality (Jaszczak) phantom and a striatal phantom were filled with F-18 and positioned in END and CEN locations. For each phantom and each location, we acquired a ∼1-hr listmode PET, rebinned the data into 10 frames with equal number of coincidence events, and reconstructed each frame using an iterative algorithm. For the striatal phantom, END and CEN were compared by drawing on each image three regions of interest (ROI) in axially separated uniform areas. The standard deviation of the activity estimation within each ROI was averaged over the 10 images. The coefficient of variation (CV) for activity estimation was calculated at each position. Image quality was assessed by inspecting the resolution bar pattern in the Jaszczak phantom at two different head positions. Results: The CV was the lowest for ROIs near the center of the FOV. For slices near the end, not only was the CV highest, but also the resolution pattern was degraded. CTDIvol summarized in the dose report indicated that the CT dose was ∼ 10% higher for CEN as compared to END position. Conclusion: Positioning the brain in the middle of the FOV in a large FOV PET/CT scanner allows more precise measurement of tracer uptake and better image quality at the cost of increased CT dose. For the end location longer scan times may minimize image quality degradation without any additional CT dose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

SATYA: Defending Against Adversarial Attacks Using Statistical HypothesisTesting

The paper presents a new defense against adversarial attacks for deep neural networks. We demonstrate the effectiveness of our approach against the popular adversarial image generation method DeepFool. Our approach uses Wald’s Sequential Probability Ratio Test to sufficiently sample a carefully chosen neighborhood around an input image to determine the correct label of the image. On a benchmark of 50,000 randomly chosen adversarial images generated by DeepFool we demonstrate that our method SATYA is able to recover the correct labels for 95.76% of the images for CaffeNet and 97.43% of the correct label for GoogLeNet.

Raj, Sunny↗
DOE OSTI2025

A bi-channel aided stitching of atomic force microscopy images

Microscopy is an essential tool in scientific research, enabling the visualization of structures at micro- and nanoscale resolutions. However, the field of microscopy often encounters limitations in field-of-view (FOV), restricting the amount of sample that can be imaged in a single capture. To overcome this limitation, image stitching techniques have been developed to seamlessly merge multiple overlapping images into a single, high-resolution composite. The images collected from microscope need to be optimally stitched before accurate physical information can be extracted from post analysis. However, the existing stitching tools either struggle to stitch images together when the microscopy images are feature sparse or cannot address all the transformations of images when performing image stitching. To address these issues, we propose a bi-channel aided feature-based image stitching method and demonstrate its use on Atomic Force Microscopy (AFM) generated Pantoea sp. YR343 biofilm and PTO thin film sample images as experimental data. The topographical channel image of AFM data captures the morphological details of the sample, and a stitched topographical image is desired for researchers. We utilize the amplitude and phase channels of AFM data to maximize the matching features and to estimate the position of the original topographical images and show that the proposed bi-channel aided stitching method outperforms the traditional direct stitching approach in AFM topographical image stitching task. Here, we demonstrated the application on AFM, but similar approaches could be employed of optical microscopy with brightfield and fluorescence channels. We believe this proposed workflow can serve as a valuable augmentation strategy for microscopy image stitching tasks and will benefit the experimentalist to avoid erroneous analysis and discovery due to incorrect stitching.

Atomic force microscopy↗
DOE OSTI2018

System and method for controlling depth of imaging in tissues using fluorescence microscopy under ultraviolet excitation following staining with fluorescing agents

A method is disclosed for analyzing a thin tissue sample and adapted to be supported on a slide. The tissue sample may be placed on a slide and exposed to one or more different exogenous fluorophores excitable in a range of about 300 nm-200 nm, and having a useful emission band from about 350 nm-900 nm, and including one or more fluorescent dyes or fluorescently labeled molecular probes that accumulate in tissue or cellular components. The fluorophores may be excited with a first wavelength of UV light between about 200 nm-290 nm. An optical system collects emissions from the fluorophores at a second wavelength, different from the first wavelength, which are generated in response to the first wavelength of UV light, to produce an image for analysis.

47 OTHER INSTRUMENTATION↗
NASA NTRS2007

A Software Platform for Post-Processing Waveform-Based NDE

Ultrasonic, microwave, and terahertz nondestructive evaluation imaging systems generally require the acquisition of waveforms at each scan point to form an image. For such systems, signal and image processing methods are commonly needed to extract information from the waves and improve resolution of, and highlight, defects in the image. Since some similarity exists for all waveform-based NDE methods, it would seem a common software platform containing multiple signal and image processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. This presentation describes NASA Glenn Research Center's approach in developing a common software platform for processing waveform-based NDE signals and images. This platform is currently in use at NASA Glenn and at Lockheed Martin Michoud Assembly Facility for processing of pulsed terahertz and ultrasonic data. Highlights of the software operation will be given. A case study will be shown for use with terahertz data. The authors also request scientists and engineers who are interested in sharing customized signal and image processing algorithms to contribute to this effort by letting the authors code up and include these algorithms in future releases.

Roth, Donald J.↗
DOE OSTI2025

Scaling deep learning for material imaging with a pseudo 3D model for domain transfer

The recent introduction of deep learning methods for image processing has greatly advanced the characterization of materials using three-dimensional (3D) X-ray imaging techniques. However, deep learning models often have difficulty performing consistently across images owing to unavoidable variations in imaging conditions, which create inconsistencies even for the same material. As a result, networks must frequently be retrained for new datasets, limiting their applicability and generalization. Thus, it is critical to reduce the variations between images to enable a single model to process multiple datasets. Herein, we introduce P3T-Net, a pseudo-3D domain transfer network that transfers diverse 3D images into a uniform domain before processing using deep learning models. Remarkably, P3T-Net enables the reuse of previously trained networks for processing new images and considerably reduces the computational cost of transferring 3D images across domains. These unique capabilities were demonstrated in the following scenarios: (i) image enhancement of fast scans for geological rock and hydrogen fuel cells, (ii) enhancement of images to match the quality of multi-source imaging for lithium-ion batteries, (iii) accurate segmentation of images captured under different conditions, and (iv) tera-scale 3D transfer (10 11 voxels) on a single GPU. Overall, the proposed approach addresses cross-domain inconsistencies across various materials and conditions, thereby enabling more robust and generalizable deep learning solutions for a wide range of material imaging tasks.

25 ENERGY STORAGE↗
DOE OSTI2013

CT head-scan dosimetry in an anthropomorphic phantom and associated measurement of ACR accreditation-phantom imaging metrics under clinically representative scan conditions

Purpose: To measure radiation absorbed dose and its distribution in an anthropomorphic head phantom under clinically representative scan conditions in three widely used computed tomography (CT) scanners, and to relate those dose values to metrics such as high-contrast resolution, noise, and contrast-to-noise ratio (CNR) in the American College of Radiology CT accreditation phantom.Methods: By inserting optically stimulated luminescence dosimeters (OSLDs) in the head of an anthropomorphic phantom specially developed for CT dosimetry (University of Florida, Gainesville), we measured dose with three commonly used scanners (GE Discovery CT750 HD, Siemens Definition, Philips Brilliance 64) at two different clinical sites (Walter Reed National Military Medical Center, National Institutes of Health). The scanners were set to operate with the same data-acquisition and image-reconstruction protocols as used clinically for typical head scans, respective of the practices of each facility for each scanner. We also analyzed images of the ACR CT accreditation phantom with the corresponding protocols. While the Siemens Definition and the Philips Brilliance protocols utilized only conventional, filtered back-projection (FBP) image-reconstruction methods, the GE Discovery also employed its particular version of an adaptive statistical iterative reconstruction (ASIR) algorithm that can be blended in desired proportions with the FBP algorithm. We did an objective image-metrics analysis evaluating the modulation transfer function (MTF), noise power spectrum (NPS), and CNR for images reconstructed with FBP. For images reconstructed with ASIR, we only analyzed the CNR, since MTF and NPS results are expected to depend on the object for iterative reconstruction algorithms.Results: The OSLD measurements showed that the Siemens Definition and the Philips Brilliance scanners (located at two different clinical facilities) yield average absorbed doses in tissue of 42.6 and 43.1 mGy, respectively. The GE Discovery delivers about the same amount of dose (43.7 mGy) when run under similar operating and image-reconstruction conditions, i.e., without tube current modulation and ASIR. The image-metrics analysis likewise showed that the MTF, NPS, and CNR associated with the reconstructed images are mutually comparable when the three scanners are run with similar settings, and differences can be attributed to different edge-enhancement properties of the applied reconstruction filters. Moreover, when the GE scanner was operated with the facility's scanner settings for routine head exams, which apply 50% ASIR and use only approximately half of the 100%-FBP dose, the CNR of the images showed no significant change. Even though the CNR alone is not sufficient to characterize the image quality and justify any dose reduction claims, it can be useful as a constancy test metric.Conclusions: This work presents a straightforward method to connect direct measurements of CT dose with objective image metrics such as high-contrast resolution, noise, and CNR. It demonstrates that OSLD measurements in an anthropomorphic head phantom allow a realistic and locally precise estimation of magnitude and spatial distribution of dose in tissue delivered during a typical CT head scan. Additional objective analysis of the images of the ACR accreditation phantom can be used to relate the measured doses to high contrast resolution, noise, and CNR.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

A Test of ASTM Methods E1245-03 and E562-11 in Calculating the Volume Fraction of Carbides in a U-10Mo Foil

Volume fraction measurements of carbides in DU-10Mo castings and foils were performed as part of a round robin study aimed at ensuring characterization efforts by multiple laboratories were yielding consistent results. Three of the four labs employed an automatic image analysis method to determine volume fraction of carbides in the metal and reported results around 2%. The other laboratory used a grid intercept count method and reported a fraction percentage of above 5%, about 3% higher than the other labs. At LANL, the method ASTM E1245-03, Determining the Inclusion or Second-Phase Constituent Content of Metals by Automatic Image Analysis was employed with a result of 2.02 ± .26%. There was a need to resolve the large discrepancy in volume fraction measurements reported from the round robin participant that used the grid intercept method. To do this, the grid intercept method outlined in ASTM E562-11, Determining Volume Fraction by Systematic Manual Point Count was also performed on the exact set of micrographs already analyzed by image analysis software at LANL. Calculations carried out following the manual point count method reported a percentage of 2.2 ± .6% similar to the result yielded by the automated image analysis method. Explanations for discrepancies in the results of the two methods are proposed.

36 MATERIALS SCIENCE↗