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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data

The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized forest AGB sampling errors by 15 - 38%. Furthermore, spaceborne global scale accuracy requirements were achieved. At least 80% of the grid cells at 100m, 250m, 500m, and 1km grid levels met AGB density accuracy requirements using a combination of passive optical and SAR along with machine learning methods to predict vegetation structure metrics for forested areas without LiDAR samples. Finally, using either passive optical or SAR, accuracy requirements were met at the 500m and 250m grid level, respectively.

Montesano, P. M.↗
DOE OSTI2015

SPEQTACLE: An automated generalized fuzzy C-means algorithm for tumor delineation in PET

Purpose: Accurate tumor delineation in positron emission tomography (PET) images is crucial in oncology. Although recent methods achieved good results, there is still room for improvement regarding tumors with complex shapes, low signal-to-noise ratio, and high levels of uptake heterogeneity. Methods: The authors developed and evaluated an original clustering-based method called spatial positron emission quantification of tumor—Automatic Lp-norm estimation (SPEQTACLE), based on the fuzzy C-means (FCM) algorithm with a generalization exploiting a Hilbertian norm to more accurately account for the fuzzy and non-Gaussian distributions of PET images. An automatic and reproducible estimation scheme of the norm on an image-by-image basis was developed. Robustness was assessed by studying the consistency of results obtained on multiple acquisitions of the NEMA phantom on three different scanners with varying acquisition parameters. Accuracy was evaluated using classification errors (CEs) on simulated and clinical images. SPEQTACLE was compared to another FCM implementation, fuzzy local information C-means (FLICM) and fuzzy locally adaptive Bayesian (FLAB). Results: SPEQTACLE demonstrated a level of robustness similar to FLAB (variability of 14% ± 9% vs 14% ± 7%, p = 0.15) and higher than FLICM (45% ± 18%, p < 0.0001), and improved accuracy with lower CE (14% ± 11%) over both FLICM (29% ± 29%) and FLAB (22% ± 20%) on simulated images. Improvement was significant for the more challenging cases with CE of 17% ± 11% for SPEQTACLE vs 28% ± 22% for FLAB (p = 0.009) and 40% ± 35% for FLICM (p < 0.0001). For the clinical cases, SPEQTACLE outperformed FLAB and FLICM (15% ± 6% vs 37% ± 14% and 30% ± 17%, p < 0.004). Conclusions: SPEQTACLE benefitted from the fully automatic estimation of the norm on a case-by-case basis. This promising approach will be extended to multimodal images and multiclass estimation in future developments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-04: 3D Dose Based Patient Compensator QA Procedure for Proton Radiotherapy

Purpose: In proton double-scattering radiotherapy, compensators are the essential patient specific devices to contour the distal dose distribution to the tumor target. Traditional compensator QA is limited to checking the drilled surface profiles against the plan. In our work, a compensator QA process was established that assess the entire compensator including its internal structure for patient 3D dose verification. Methods: The fabricated patient compensators were CT scanned. Through mathematical image processing and geometric transformations, the CT images of the proton compensator were combined with the patient simulation CT images into a new series of CT images, in which the imaged compensator is placed at the planned location along the corresponding beam line. The new CT images were input into the Eclipse treatment planning system. The original plan was calculated to the combined CT image series without the plan compensator. The newly computed patient 3D dose from the combined patientcompensator images was verified against the original plan dose. Test plans include the compensators with defects intentionally created inside the fabricated compensators. Results: The calculated 3D dose with the combined compensator and patient CT images reflects the impact of the fabricated compensator to the patient. For the test cases in which no defects were created, the dose distributions were in agreement between our method and the corresponding original plans. For the compensator with the defects, the purposely changed material and a purposely created internal defect were successfully detected while not possible with just the traditional compensator profiles detection methods. Conclusion: We present here a 3D dose verification process to qualify the fabricated proton double-scattering compensator. Such compensator detection process assesses the patient 3D impact of the fabricated compensator surface profile as well as the compensator internal material and structure changes. This research receives funding support from CURA Medical Technologies.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1973

Developments in electronic imaging techniques; Proceedings of the Seminar-in-Depth, San Mateo, Calif., October 16, 17, 1972.

Capabilities and limitations of infrared imaging systems are discussed, and a real-time simulator for image data systems is described. Ultrahigh resolution electronic imaging and storage with the return beam vidicon is treated, and a description is given of an electron-lens for opaque photocathodes. Ground surveillance with an active low light level TV, digital processing of Mariner 9 TV data, image enhancement by holography, and application of data compression techniques to spacecraft imaging systems are given attention. Individual items are announced in this issue.

Zirkind, R.↗
NASA NTRS2016

High Resolution Image Reconstruction from Projection of Low Resolution Images DIffering in Subpixel Shifts

In this paper, we demonstrate a simple algorithm that projects low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithm is very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. used in projection yield comparable results. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML), and Maximum a posterior (MAP) algorithms. The algorithm is robust and is not overly sensitive to the registration inaccuracies.

0↗
DOE OSTI2014

3-Dimensional Magnetic Resonance Spectroscopic Imaging at 3 Tesla for Early Response Assessment of Glioblastoma Patients During External Beam Radiation Therapy

Purpose: To evaluate the utility of 3-dimensional magnetic resonance (3D-MR) proton spectroscopic imaging for treatment planning and its implications for early response assessment in glioblastoma multiforme. Methods and Materials: Eighteen patients with newly diagnosed, histologically confirmed glioblastoma had 3D-MR proton spectroscopic imaging (MRSI) along with T2 and T1 gadolinium-enhanced MR images at simulation and at boost treatment planning after 17 to 20 fractions of radiation therapy. All patients received standard radiation therapy (RT) with concurrent temozolomide followed by adjuvant temozolomide. Imaging for response assessment consisted of MR scans every 2 months. Progression-free survival was defined by the criteria of MacDonald et al. MRSI images obtained at initial simulation were analyzed for choline/N-acetylaspartate ratios (Cho/NAA) on a voxel-by-voxel basis with abnormal activity defined as Cho/NAA ≥2. These images were compared on anatomically matched MRSI data collected after 3 weeks of RT. Changes in Cho/NAA between pretherapy and third-week RT scans were tested using Wilcoxon matched-pairs signed rank tests and correlated with progression-free survival, radiation dose and location of recurrence using Cox proportional hazards regression. Results: After a median follow-up time of 8.6 months, 50% of patients had experienced progression based on imaging. Patients with a decreased or stable mean or median Cho/NAA values had less risk of progression (P<.01). Patients with an increase in mean or median Cho/NAA values at the third-week RT scan had a significantly greater chance of early progression (P<.01). An increased Cho/NAA at the third-week MRSI scan carried a hazard ratio of 2.72 (95% confidence interval, 1.10-6.71; P=.03). Most patients received the prescription dose of RT to the Cho/NAA ≥2 volume, where recurrence most often occurred. Conclusion: Change in mean and median Cho/NAA detected at 3 weeks was a significant predictor of early progression. The potential impact for risk-adaptive therapy based on early spectroscopic findings is suggested.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Mesoscale Linear Elastic Modeling and Homogenization of Marine Energy Composites

The design of fiber-reinforced composite (FRC)-based components for marine energy applications necessitates a fundamental understanding of material properties and the resulting geometry to predict long-term performance. In this work, we present a modeling workflow to predict linear elastic and diffusive bulk properties at the mesoscale for an idealized geometry based on knowledge of fiber and resin properties. A parametric study was performed to identify the key model input parameters that influence bulk properties. Furthermore, we demonstrate how bulk properties can be leveraged in high-fidelity image-based simulations, where imperfections in tow geometry and voids captured during X-ray computed tomography imaging are explicitly represented within the simulation. Bulk properties of interest include moduli, Poisson’s ratios, hygroscopic swelling, diffusivity, and moisture uptake, which are key parameters for characterizing FRC performance within marine environments. Modeling predictions agreed well with experimental data, except for estimating swelling coefficients, likely due to crack accumulation as a function of moisture uptake. The mesoscale modeling workflow ultimately highlights a versatile framework for understanding the influence of material and geometric properties, which can be leveraged to rapidly assess new FRC-based components.

computational mechanics↗
DOE OSTI2015

SU-E-J-140: Simulation Study Using Thermoacoustics to Image Proton Dose and Range in Water and Skull Phantom

Purpose: In this study, thermoacoustic pressure signals generated from a proton beam were simulated in water and currently within a skull phantom to investigate the sensitivity of radioacoustic CT imaging in the brain. Methods: Thermoacoustically generated pressure signals from a pulse pencil proton beam (12, 15, 20, and 27cm range) were simulated in water. These simulated pressure signal are detected using a (71) transducer array placed along the surface of a cylinder (30cm × 40cm) and rotated over 2π (in 2 degree increments), where the normal vector to the surface of each transducer intersects the isocenter of the scanner. Currently, a software skull phantom is positioned at isocenter, where the scattering, absorption and speed of dispersion of the thermoacoustic signal through a three layer cortical-trabecular-cortical structure is being simulated. Based on data obtained from the literature, the effects of acoustic attenuation and speed-of-sound (dispersion) will be applied within the 3D FBP algorithm to obtain dosimetric images. Results: Based on hydrophone detector specifications, a 0.5MHz bandwidth and 50dB re 1μPa per Hz^1/2, a 1.6cGy sensitivity at the Bragg peak was demonstrated while maintaining a 1.0 mm (FWHM) range resolution along the central axis of the beam. Utilizing this same information, the integral dose within the Bragg peak and distal edge compared to MC had a 2% (statistical) and 5% voxel-based RMS at this same dose sensitivity. We plan to present preliminary data determining the range sensitivity for a head phantom for this scanner design and the feasibility of imaging the proton dose in patients with a brain tumor undergoing therapy. Conclusion: RACT scanner provides 3D dosimetric images with 1.6cGy (Bragg peak) sensitivity with 1mm range sensitivity. Simulations will be performed to determine feasibility to treat brain cancer patients.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1979

Geologic applications of thermal inertia image using HCMM data

The author has identified the following significant results. Comparison of a simulated HCMM image of the Pisgah Crater, California test site obtained from aircraft data with an image generated from the preliminary satellite data tape of the area indicates that the HCMM satellite data appears much as predicted by the simulation.

Kahle, A. B.↗
DOE OSTI2014

SU-E-J-82: Intra-Fraction Proton Beam-Range Verification with PET Imaging: Feasibility Studies with Monte Carlo Simulations and Statistical Modeling

Purpose: To study the feasibility of intra-fraction proton beam-range verification with PET imaging. Methods: Two phantoms homogeneous cylindrical PMMA phantoms (290 mm axial length, 38 mm and 200 mm diameter respectively) were studied using PET imaging: a small phantom using a mouse-sized PET (61 mm diameter field of view (FOV)) and a larger phantom using a human brain-sized PET (300 mm FOV). Monte Carlo (MC) simulations (MCNPX and GATE) were used to simulate 179.2 MeV proton pencil beams irradiating the two phantoms and be imaged by the two PET systems. A total of 50 simulations were conducted to generate 50 positron activity distributions and correspondingly 50 measured activity-ranges. The accuracy and precision of these activity-ranges were calculated under different conditions (including count statistics and other factors, such as crystal cross-section). Separate from the MC simulations, an activity distribution measured from a simulated PET image was modeled as a noiseless positron activity distribution corrupted by Poisson counting noise. The results from these two approaches were compared to assess the impact of count statistics on the accuracy and precision of activity-range calculations. Results: MC Simulations show that the accuracy and precision of an activity-range are dominated by the number (N) of coincidence events of the reconstructed image. They are improved in a manner that is inversely proportional to 1/sqrt(N), which can be understood from the statistical modeling. MC simulations also indicate that the coincidence events acquired within the first 60 seconds with 10{sup 9} protons (small phantom) and 10{sup 10} protons (large phantom) are sufficient to achieve both sub-millimeter accuracy and precision. Conclusion: Under the current MC simulation conditions, the initial study indicates that the accuracy and precision of beam-range verification are dominated by count statistics, and intra-fraction PET image-based beam-range verification is feasible. This work was supported by a research award RP120326 from Cancer Prevention and Research Institute of Texas.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Application of deep neural networks to improve diagnostic accuracy of rheumatoid arthritis using diffuse optical tomography

A set of deep neural network models for rheumatoid arthritis (RA) classification using a highway network, a convolutional neural network and a residual network is proposed based on the data of diffuse optical tomography (DOT) utilising near-infrared light, which ensures early diagnosis of pathophysiological changes resulting from inflammation. A numerical model of the finger is used to generate images to overcome the inherent problem of insufficient clinical DOT images available. The proposed deep neural network models are applied to automatically classify simulated DOT images of inflamed and non-inflamed joints and transfer learning is also used to improve the performance of the classification. The results demonstrate that all three deep neural network methods improve the diagnostic accuracy as compared to the widely applied support vector machine (SVM), especially for high inter-subject variability databases. In cases of distinct modelled severity of disease, residual network achieved the highest accuracy (> 99 %), and both of highway and convolutional neural networks reached 99 %, respectively. However, as the severity of the modelled disease is reduced, this accuracy is reduced to 75.2 % for residual networks. The results indicate that transfer learning can improve the performance of deep neural network methods on RA classification from DOT data and highlight their potential as a computer aided tool in DOT diagnostic systems. (paper)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Impact of simulated reduced injected dose on the assessment of amyloid PET scans

To investigate the impact of reduced injected doses on the quantitative and qualitative assessment of the amyloid PET tracers [ 18 F]flutemetamol and [ 18 F]florbetaben. Cognitively impaired and unimpaired individuals (N = 250, 36% Aβ-positive) were included and injected with [ 18 F]flutemetamol (N = 175) or [ 18 F]florbetaben (N = 75). PET scans were acquired in list-mode (90–110 min post-injection) and reduced-dose images were simulated to generate images of 75, 50, 25, 12.5 and 5% of the original injected dose. Images were reconstructed using vendor-provided reconstruction tools and visually assessed for Aβ-pathology. SUVRs were calculated for a global cortical and three smaller regions using a cerebellar cortex reference tissue, and Centiloid was computed. Absolute and percentage differences in SUVR and CL were calculated between dose levels, and the ability to discriminate between Aβ- and Aβ + scans was evaluated using ROC analyses. Finally, intra-reader agreement between the reduced dose and 100% images was evaluated. At 5% injected dose, change in SUVR was 3.72% and 3.12%, with absolute change in Centiloid 3.35CL and 4.62CL, for [ 18 F]flutemetamol and [ 18 F]florbetaben, respectively. At 12.5% injected dose, percentage change in SUVR and absolute change in Centiloid were < 1.5%. AUCs for discriminating Aβ- from Aβ + scans were high (AUC ≥ 0.94) across dose levels, and visual assessment showed intra-reader agreement of > 80% for both tracers. This proof-of-concept study showed that for both [ 18 F]flutemetamol and [ 18 F]florbetaben, adequate quantitative and qualitative assessments can be obtained at 12.5% of the original injected dose. However, decisions to reduce the injected dose should be made considering the specific clinical or research circumstances.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

A Fully Automated Method for CT-on-Rails-Guided Online Adaptive Planning for Prostate Cancer Intensity Modulated Radiation Therapy

Purpose: This study was designed to validate a fully automated adaptive planning (AAP) method which integrates automated recontouring and automated replanning to account for interfractional anatomical changes in prostate cancer patients receiving adaptive intensity modulated radiation therapy (IMRT) based on daily repeated computed tomography (CT)-on-rails images. Methods and Materials: Nine prostate cancer patients treated at our institution were randomly selected. For the AAP method, contours on each repeat CT image were automatically generated by mapping the contours from the simulation CT image using deformable image registration. An in-house automated planning tool incorporated into the Pinnacle treatment planning system was used to generate the original and the adapted IMRT plans. The cumulative dose–volume histograms (DVHs) of the target and critical structures were calculated based on the manual contours for all plans and compared with those of plans generated by the conventional method, that is, shifting the isocenters by aligning the images based on the center of the volume (COV) of prostate (prostate COV-aligned). Results: The target coverage from our AAP method for every patient was acceptable, while 1 of the 9 patients showed target underdosing from prostate COV-aligned plans. The normalized volume receiving at least 70 Gy (V{sub 70}), and the mean dose of the rectum and bladder were reduced by 8.9%, 6.4 Gy and 4.3%, 5.3 Gy, respectively, for the AAP method compared with the values obtained from prostate COV-aligned plans. Conclusions: The AAP method, which is fully automated, is effective for online replanning to compensate for target dose deficits and critical organ overdosing caused by interfractional anatomical changes in prostate cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Aberration-free imaging of inelastic-scattering spectra with x-ray echo spectrometers

We study here conditions for aberration-free imaging of inelastic x-ray-scattering (IXS) spectra with x-ray echo spectrometers. Aberration-free imaging is essential for achieving instrumental functions with high resolution and high contrast. Computational ray tracing is applied to a thorough analysis of a $0.1\mathrm{meV}/0.07{-}{\mathrm{nm}}^{{-}1}$-resolution echo-type IXS spectrometer operating with 9-keV x rays. We show that IXS spectra imaged by the x-ray echo spectrometer that uses lenses for the collimating and focusing optics are free of aberrations. When grazing incidence mirrors (paraboloidal, parabolic Kirkpatrick-Baez, or parabolic Montel) are used instead of the lenses, the imaging system reveals some defocus aberration that depends on the inelastic energy transfer. However, the aberration-free images can be still recorded in a plane that is tilted with respect to the optical axis. This distortion can be thus fully compensated by inclining appropriately the x-ray imaging detector, which simultaneously improves its spatial resolution. A full simulation of imaging IXS spectra from a realistic sample demonstrates the excellent performance of the proposed designs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

SU-C-202-05: Pilot Study of Online Treatment Evaluation and Adaptive Re-Planning for Laryngeal SBRT

Purpose: We have instigated a phase I trial of 5-fraction stereotactic body radiotherapy (SBRT) for advanced-stage laryngeal cancer. We conducted this pilot dosimetric study to confirm the potential utility of online adaptive re-planning to preserve treatment quality. Methods: Ten cases of larynx cancer were evaluated. Baseline and daily SBRT treatment plans were generated per trial protocol. Daily volumetric images were acquired prior to every fraction of treatment. Reference simulation CT images were deformably registered to daily volumetric images using Eclipse. Planning contours were then deformably propagated to daily images. Reference SBRT plans were directly copied to calculate delivered dose distributions on deformed reference CT images. In-house software platform has been developed to calculate cumulative dose over a course of treatment in four steps: 1) deforming delivered dose grid to reference CT images using deformation information exported from Eclipse; 2) generating tetrahedrons using deformed dose grid as vertices; 3) resampling dose to a high resolution within every tetrahedron; 4) calculating dose-volume histograms. Our inhouse software was benchmarked with a commercial software, Mirada. Results: In all ten cases including 49 fractions of treatments, delivered daily doses were completely evaluated and treatment could be re-planned within 10 minutes. Prescription dose coverage of PTV was less than intended in 53% of fractions of treatment (mean: 94%, range: 84%–98%) while minimum coverage of CTV and GTV was 94% and 97%, respectively. Maximum bystander point dose limits to arytenoids, parotids, and spinal cord remained respected in all cases, although variances in carotid artery doses were observed in a minority of cases. Conclusion: Although GTV and CTV coverage is preserved by in-room 3D image guidance of larynx SBRT, PTV coverage can vary significantly from intended plans. Online adaptive treatment evaluation and re-planning is potentially necessary and our procedure is clinically applicable to fully preserve treatment quality. This project is supported by CPRIT Individual Investigator Research Award RP150386.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Kilovoltage energy imaging with a radiotherapy linac with a continuously variable energy range

Purpose: In this paper, the effect on image quality of significantly reducing the primary electron energy of a radiotherapy accelerator is investigated using a novel waveguide test piece. The waveguide contains a novel variable coupling device (rotovane), allowing for a wide continuously variable energy range of between 1.4 and 9 MeV suitable for both imaging and therapy.Method: Imaging at linac accelerating potentials close to 1 MV was investigated experimentally and via Monte Carlo simulations. An imaging beam line was designed, and planar and cone beam computed tomography images were obtained to enable qualitative and quantitative comparisons with kilovoltage and megavoltage imaging systems. The imaging beam had an electron energy of 1.4 MeV, which was incident on a water cooled electron window consisting of stainless steel, a 5 mm carbon electron absorber and 2.5 mm aluminium filtration. Images were acquired with an amorphous silicon detector sensitive to diagnostic x-ray energies. Results: The x-ray beam had an average energy of 220 keV and half value layer of 5.9 mm of copper. Cone beam CT images with the same contrast to noise ratio as a gantry mounted kilovoltage imaging system were obtained with doses as low as 2 cGy. This dose is equivalent to a single 6 MV portal image. While 12 times higher than a 100 kVp CBCT system (Elekta XVI), this dose is 140 times lower than a 6 MV cone beam imaging system and 6 times lower than previously published LowZ imaging beams operating at higher (4-5 MeV) energies. Conclusions: The novel coupling device provides for a wide range of electron energies that are suitable for kilovoltage quality imaging and therapy. The imaging system provides high contrast images from the therapy portal at low dose, approaching that of gantry mounted kilovoltage x-ray systems. Additionally, the system provides low dose imaging directly from the therapy portal, potentially allowing for target tracking during radiotherapy treatment. There is the scope with such a tuneable system for further energy reduction and subsequent improvement in image quality.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Creating ground truth for nanocrystal morphology: a fully automated pipeline for unbiased transmission electron microscopy analysis

Control over colloidal nanocrystal morphology (size, size distribution, and shape) is important for tailoring the functionality of individual nanocrystals and their ensemble behavior. Despite this, traditional methods to quantify nanocrystal morphology are laborious. New developments in automated morphology classification will accelerate these analyses but the assessment of machine learning models is limited by human accuracy for ground truth, causing even unsupervised machine learning models to have inherent bias. Herein, we introduce synthetic image rendering to solve the ground truth problem of nanocrystal morphology classification. By simulating 2D images of nanocrystal shapes via a function of high-dimensional parameter space, we trained a convolutional neural network to link unique morphologies to their simulated parameters, defining nanocrystal morphology quantitatively rather than qualitatively. An automated pipeline then processes, quantitatively defines, and classifies nanocrystal morphology from experimental transmission electron microscopy (TEM) images. Using improved computer vision techniques, 42,650 nanocrystals were identified, assessed, and labeled with quantitative parameters, offering a 600-fold improvement in efficiency over best-practice manual measurements. Further, a classification algorithm was trained with a prediction accuracy of 99.5%, which can successfully analyze a range of concave, convex, and irregular nanocrystal shapes. The resulting pipeline was applied to differentiating two syntheses of nominally cuboidal CsPbBr 3 nanocrystals and uniquely classifying binary nickel sulfide nanocrystal phase based on morphology. This pipeline provides a simple, efficient, and unbiased method to quantify nanocrystal morphology and represents a practical route to construct large datasets with an absolute ground truth for training unbiased morphology-based machine learning algorithms.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2013

Bispectral Speckle Imaging Algorithm Performance on Specific Simulated Scenarios

The purpose of this report is to describe the anticipated performance of LLNL’s bispectral speckle imaging algorithm on specific imaging scenarios and further evaluate the regime over which bispectral speckle imaging can be used to compensate for atmospheric turbulence. This includes investigating a number of relevant Cn2 cases and multiple wavelengths. The anticipated performance described here will be evaluated based upon simulated imagery. As with any simulation, it must be realized that the full truth of the matter will be determined when real data is analyzed. This report assumes some basic familiarity with bispectral speckle imaging.

42 ENGINEERING↗