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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Core or Cusps: The Central Dark Matter Profile of a Strong Lensing Cluster with a Bright Central Image at Redshift 1

We report on SPT-CLJ2011-5228, a giant system of arcs created by a cluster at z = 1.06. The arc system is notable for the presence of a bright central image. The source is a Lyman break galaxy at z ( )s( ) = 2.39 and the mass enclosed within the Einstein ring of radius 14 arcsec is $\sim {10}^{14.2}\ {M}_{\odot }$. We perform a full reconstruction of the light profile of the lensed images to precisely infer the parameters of the mass distribution. The brightness of the central image demands that the central total density profile of the lens be shallow. By fitting the dark matter as a generalized Navarro–Frenk–White profile—with a free parameter for the inner density slope—we find that the break radius is ${270}_{-76}^{+48}$ kpc, and that the inner density falls with radius to the power −0.38 ± 0.04 at 68% confidence. Such a shallow profile is in strong tension with our understanding of relaxed cold dark matter halos, dark matter-only simulations predict that the inner density should fall as ${r}^{-1}$. The tension can be alleviated if this cluster is in fact a merger, a two-halo model can also reconstruct the data, with both clumps (density varying as ${r}^{-0.8}$ and ${r}^{-1.0}$) much more consistent with predictions from dark matter-only simulations. At the resolution of our Dark Energy Survey imaging, we are unable to choose between these two models, but we make predictions for forthcoming Hubble Space Telescope imaging that will decisively distinguish between them.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1988

Dependence of image grey values on topography in SIR-B images

This paper focuses on the use of a high resolution digital elevation model (DEM) to aid in rectifying and enhancing synthetic aperture radar images. Using a synthetic backscatter image, the SIR-B images are manually rectified and resampled to remove geometric distortions caused by topography. In a second step, an improved reflectance function of incidence angle is derived from the DEM and the rectified image and this function is used to reduce radiometric effects of topography yielding an albedo image which clearly shows the thematic, as opposed to topographic content of the image. The procedure is tested on four SIR-B images of a scene in Argentina (crossover point) that is imaged under different azimuth and incidence angles. The similarity of the resulting images indicates that the procedure effectively reduces artefacts from the images that are dependent on topography.

Domik, G.↗
DOE OSTI2015

SU-E-J-261: The Importance of Appropriate Image Preprocessing to Augment the Information of Radiomics Image Features

Purpose: To investigate how different image preprocessing techniques, their parameters, and the different boundary handling techniques can augment the information of features and improve feature’s differentiating capability. Methods: Twenty-seven NSCLC patients with a solid tumor volume and no visually obvious necrotic regions in the simulation CT images were identified. Fourteen of these patients had a necrotic region visible in their pre-treatment PET images (necrosis group), and thirteen had no visible necrotic region in the pre-treatment PET images (non-necrosis group). We investigated how image preprocessing can impact the ability of radiomics image features extracted from the CT to differentiate between two groups. It is expected the histogram in the necrosis group is more negatively skewed, and the uniformity from the necrosis group is less. Therefore, we analyzed two first order features, skewness and uniformity, on the image inside the GTV in the intensity range [−20HU, 180HU] under the combination of several image preprocessing techniques: (1) applying the isotropic Gaussian or anisotropic diffusion smoothing filter with a range of parameter(Gaussian smoothing: size=11, sigma=0:0.1:2.3; anisotropic smoothing: iteration=4, kappa=0:10:110); (2) applying the boundaryadapted Laplacian filter; and (3) applying the adaptive upper threshold for the intensity range. A 2-tailed T-test was used to evaluate the differentiating capability of CT features on pre-treatment PT necrosis. Result: Without any preprocessing, no differences in either skewness or uniformity were observed between two groups. After applying appropriate Gaussian filters (sigma>=1.3) or anisotropic filters(kappa >=60) with the adaptive upper threshold, skewness was significantly more negative in the necrosis group(p<0.05). By applying the boundary-adapted Laplacian filtering after the appropriate Gaussian filters (0.5 <=sigma<=1.1) or anisotropic filters(20<=kappa <=50), the uniformity was significantly lower in the necrosis group (p<0.05). Conclusion: Appropriate selection of image preprocessing techniques allows radiomics features to extract more useful information and thereby improve prediction models based on these features.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-D-BRA-03: Four-Dimensional Dose Reconstruction Through Retrospective Phase Determination Using Cine Images of Electronic Portal Imaging Device

Purpose: To test a method to reconstruct a four-dimensional (4D) dose distribution using the correlation of pre-calculated 4D electronic portal imaging device (EPID) images and measured cine-EPID images. Methods: 1. A phantom designed to simulate a tumor in lung (a polystyrene block with 3.0 cm diameter embedded in cork) was placed on a sinusoidally moving platform with 2 cm amplitude and 4 sec/cycle. Ten-phase 4D CT images were acquired for treatment planning and dose reconstruction. A 6MV photon beam was irradiated on the phantom with static (field size=5×8.5 cm{sup 2}) and dynamic fields (sliding windows, 10×10 cm{sup 2}, X1 MLC closing in parallel with the tumor movement). 2. 4D and 3D doses were calculated forwardly on PTV (1 cm margin). 3. Dose images on EPID under the fields were calculated for 10 phases. 4. Cine EPID images were acquired during irradiation. 5. Their acquisition times were correlated to the phases of the phantom at which irradiation occurred by inter-comparing calculated “reference” EPID images with measured images (2D gamma comparison). For the dynamic beam, the tumor was hidden under MLCs during a portion of irradiation time; the correlation performed when the tumor was visible was extrapolated. 6. Dose for each phase was reconstructed on the 4D CT images and summed over all phases. The summation was compared with forwardly calculated 4D and 3D dose distributions. Monte Carlo methods were used for all calculations. Results: For the open and dynamic beams, the 4D reconstructed doses showed the pass rates of 92.7 % and 100 %, respectively, at the isocenter plane given 3% / 3 mm criteria. The better agreement of the dynamic beam was from its dose gradient which blurred the otherwise sharp difference between forward and reconstructed doses. This also contributed slightly better agreement in DVH of PTV. Conclusion: The feasibility of 4D reconstruction was demonstrated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Stochastic image reconstruction for a dual-particle imaging system

Stochastic image reconstruction has been applied to a dual-particle imaging system being designed for nuclear safeguards applications. The dual-particle imager (DPI) is a combined Compton-scatter and neutron-scatter camera capable of producing separate neutron and photon images. The stochastic origin ensembles (SOE) method was investigated as an imaging method for the DPI because only a minimal estimation of system response is required to produce images with quality that is comparable to common maximum-likelihood methods. Here, this work contains neutron and photon SOE image reconstructions for a 252Cf point source, two mixed-oxide (MOX) fuel canisters representing point sources, and the MOX fuel canisters representing a distributed source. Simulation of the DPI using MCNPX-PoliMi is validated by comparison of simulated and measured results. Because image quality is dependent on the number of counts and iterations used, the relationship between these quantities is investigated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Integrative Quantitative-Phase and Airy Light-Sheet Imaging

Light-sheet microscopy enables considerable speed and phototoxicity gains, while quantitative-phase imaging confers label-free organelle recognition and metabolic information that are inaccessible by conventional methods. We report the fusion of these two modalities onto a standard inverted microscope that retains compatibility with microfluidics. We describe the utilization of an accelerating Airy-beam light-sheet yielding identical imaging areas with interferometry, and an application in unmasking the effects of cellular noise on metabolic compartmentalization.

Biological sciences, Biological techniques, Micros↗
DOE OSTI2024

Simulating image coaddition with the Nancy Grace Roman Space Telescope – II. Analysis of the simulated images and implications for weak lensing

One challenge for applying current weak lensing analysis tools to the Nancy Grace Roman Space Telescope is that individual images will be undersampled. Our companion paper presented an initial application of Imcom – an algorithm that builds an optimal mapping from input to output pixels to reconstruct a fully sampled combined image – on the Roman image simulations. In this paper, we measure the output noise power spectra, identify the sources of the major features in the power spectra, and show that simple analytic models that ignore sampling effects underestimate the power spectra of the coadded noise images. We compute the moments of both idealized injected stars and fully simulated stars in the coadded images, and their one- and two-point statistics. We show that the idealized injected stars have root-mean-square ellipticity errors (1–6) × 10 -4 per component depending on the band; the correlation functions are ≥2 orders of magnitude below requirements, indicating that the image combination step itself is using a small fraction of the overall Roman second moment error budget, although the fourth moments are larger and warrant further investigation. The stars in the simulated sky images, which include blending and chromaticity effects, have correlation functions near the requirement level (and below the requirement level in a wide-band image constructed by stacking all four filters). We evaluate the noise-induced biases in the ellipticities of injected stars, and explain the resulting trends with an analytical model. We conclude by enumerating the next steps in developing an image coaddition pipeline for Roman.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

SU-D-9A-07: Imaging Dose and Cancer Risk in Image-Guided Radiotherapy of Cancers

Purpose: To systematically evaluate the imaging doses and cancer risks associated with various imaging procedures involving ionizing radiation during image-guided radiotherapy of an increasingly large number of cancer patients. Methods: 141 patients (52 brain cases, 47 thoracic cases, 42 abdominal cases, aged 3 to 91 years old) treated between October 2009 and March 2010 were included in this IRB-approved retrospective study. During the whole radiotherapy course, each patient underwent at least one type of imaging procedures, i.e., kV portal, MV portal and kVCBCT, besides CT simulations. Based on Monte Carlo modeling and particle transport in human anatomy of various dimensions, the correlations between the radiation doses to the various organs-at-risk (OARs) at the head, the thoracic and the abdominal regions and one's weight, circumference, scan mAs and kVp have been obtained and used to estimate the radiation dose from a specific imaging procedure. The radiation-induced excess relative risk (ERR) was then estimated with BEIR VII formulism based on one's gender, age and radiation dose. 1+ ERR was reported in this study as relative cancer risk. Results: For the whole cohort of 141 patients, the mean imaging doses from various imaging procedures were 8.3 cGy to the brain, 10.5 cGy to the lungs and 19.2 cGy to the red bone marrow, respectively. Accordingly, the cancer risks were 1.140, 1.369 and 2.671, respectively. In comparison, MV portal deposited largest doses to the lungs while kVCBCT delivered the highest doses to the red bone marrow. Conclusion: The compiled imaging doses to a patient during his/her treatment course were patient-specific and site-dependent, varying from 1.2 to 263.5 cGy on average, which were clinically significant and should be included in the treatment planning and overall decision-making. Our results indicated the necessity of personalized imaging to maximize its clinical benefits while reducing the associated cancer risks. Sichuan University Scholarship.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-13: Six Degree of Freedom Image Fusion Accuracy for Cranial Target Localization On the Varian Edge Stereotactic Radiosurgery System: Comparison Between 2D/3D and KV CBCT Image Registration

Purpose: To determine the 6 degree of freedom systematic deviations between 2D/3D and CBCT image registration with various imaging setups and fusion algorithms on the Varian Edge Linac. Methods: An anthropomorphic head phantom with radio opaque targets embedded was scanned with CT slice thicknesses of 0.8, 1, 2, and 3mm. The 6 DOF systematic errors were assessed by comparing 2D/3D (kV/MV with CT) with 3D/3D (CBCT with CT) image registrations with different offset positions, similarity measures, image filters, and CBCT slice thicknesses (1 and 2 mm). The 2D/3D registration accuracy of 51 fractions for 26 cranial SRS patients was also evaluated by analyzing 2D/3D pre-treatment verification taken after 3D/3D image registrations. Results: The systematic deviations of 2D/3D image registration using kV- kV, MV-kV and MV-MV image pairs were within ±0.3mm and ±0.3° for translations and rotations with 95% confidence interval (CI) for a reference CT with 0.8 mm slice thickness. No significant difference (P>0.05) on target localization was observed between 0.8mm, 1mm, and 2mm CT slice thicknesses with CBCT slice thicknesses of 1mm and 2mm. With 3mm CT slice thickness, both 2D/3D and 3D/3D registrations performed less accurately in longitudinal direction than thinner CT slice thickness (0.60±0.12mm and 0.63±0.07mm off, respectively). Using content filter and using similarity measure of pattern intensity instead of mutual information, improved the 2D/3D registration accuracy significantly (P=0.02 and P=0.01, respectively). For the patient study, means and standard deviations of residual errors were 0.09±0.32mm, −0.22±0.51mm and −0.07±0.32mm in VRT, LNG and LAT directions, respectively, and 0.12°±0.46°, −0.12°±0.39° and 0.06°±0.28° in RTN, PITCH, and ROLL directions, respectively. 95% CI of translational and rotational deviations were comparable to those in phantom study. Conclusion: 2D/3D image registration provided on the Varian Edge radiosurgery, 6 DOF-based system provides accurate target positioning for frameless image-guided cranial stereotactic radiosurgery.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-G-207-06: 3D Fluoroscopic Image Generation From Patient-Specific 4DCBCT-Based Motion Models Derived From Physical Phantom and Clinical Patient Images

Purpose: Respiratory-correlated cone-beam CT (4DCBCT) images acquired immediately prior to treatment have the potential to represent patient motion patterns and anatomy during treatment, including both intra- and inter-fractional changes. We develop a method to generate patient-specific motion models based on 4DCBCT images acquired with existing clinical equipment and used to generate time varying volumetric images (3D fluoroscopic images) representing motion during treatment delivery. Methods: Motion models are derived by deformably registering each 4DCBCT phase to a reference phase, and performing principal component analysis (PCA) on the resulting displacement vector fields. 3D fluoroscopic images are estimated by optimizing the resulting PCA coefficients iteratively through comparison of the cone-beam projections simulating kV treatment imaging and digitally reconstructed radiographs generated from the motion model. Patient and physical phantom datasets are used to evaluate the method in terms of tumor localization error compared to manually defined ground truth positions. Results: 4DCBCT-based motion models were derived and used to generate 3D fluoroscopic images at treatment time. For the patient datasets, the average tumor localization error and the 95th percentile were 1.57 and 3.13 respectively in subsets of four patient datasets. For the physical phantom datasets, the average tumor localization error and the 95th percentile were 1.14 and 2.78 respectively in two datasets. 4DCBCT motion models are shown to perform well in the context of generating 3D fluoroscopic images due to their ability to reproduce anatomical changes at treatment time. Conclusion: This study showed the feasibility of deriving 4DCBCT-based motion models and using them to generate 3D fluoroscopic images at treatment time in real clinical settings. 4DCBCT-based motion models were found to account for the 3D non-rigid motion of the patient anatomy during treatment and have the potential to localize tumor and other patient anatomical structures at treatment time even when inter-fractional changes occur. This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc., Palo Alto, CA. The project was also supported, in part, by Award Number R21CA156068 from the National Cancer Institute.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-AB-202-06: BEST IN PHYSICS (JOINT IMAGING-THERAPY): A Real-Time Tumor Tracking Using Novel Scatter Imaging Modality During Lung SBRT

Purpose: Compared to traditional radiotherapy techniques, stereotactic body radiation therapy (SBRT) provides more favorable outcomes during the treatment of certain lung tumors. Despite advancements in image guidance, accurate target localization still remains a challenge. In this work, we expand our knowledge of a novel scatter imaging modality in order to develop a real-time tumor localization method using scattered photons from the patient during treatment. Methods: Images of the QUASAR™ Respiratory Motion Phantom were taken by irradiating it on a Varian TrueBeam accelerator. The scattered radiation was detected using a flat panel-based pinhole camera detection system. Two motion settings were investigated: static and dynamic. In the former, the lung tumor was manually shifted between imaging. In the latter, the lung tumor was set to move at a certain frequency and amplitude while the images were acquired continuously for one minute. The accuracy of tumor localization and the irradiation time required to distinguish the lung tumor were studied. Results: The comparison of measured and expected location of the lung tumor during static motion was shown to be under standard deviation (STD) of 0.064 with a mean STD of 0.031cm. The dynamic motion was taken at a rate of 1400 MU/min for one minute and the measured location of the lung tumor was then compared with the QUASAR phantom’s sinusoidal motion pattern and the agreement found to be at an average STD of 0.275cm. The location of the lung tumor was investigated using aggregate images consisting of 1 or 2 frames/image and the change was below STD of 0.30cm. The lung tumor also appeared to be blurrier in images consisting of two frames. Conclusion: Based on our preliminary results real-time image guidance using the scatter imaging modality to localize and track tumors during lung SBRT has the potential to become clinical reality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Source shape estimation for neutron imaging systems using convolutional neural networks

Neutron imaging systems are important diagnostic tools for characterizing the physics of inertial confinement fusion reactions at the National Ignition Facility (NIF). In particular, neutron images give diagnostic information on the size, symmetry, and shape of the fusion hot spot and surrounding cold fuel. Images are formed via collection of neutron flux from the source using a system of aperture arrays and scintillator-based detectors. Currently, reconstruction of fusion source geometry from the collected neutron images is accomplished by solving a computationally intensive maximum likelihood estimation problem via expectation maximization. In contrast, it is often useful to have simple representations of the overall source geometry that can be computed quickly. In this work, we develop convolutional neural networks (CNNs) to reconstruct the outer contours of simple source geometries. We compare the performance of the CNN for penumbral and pinhole data and provide experimental demonstrations of our methods on both non-noisy and noisy data.

Machine learning, neutron imaging, source reconstr↗
DOE OSTI2015

SU-E-I-84: Accuracy Comparison of Multi-Modality Image-Based Volumes of Rodent Solid Tumors Using In-Air Micro-CT Image Volume

Purpose: Tumor volume is considered as a better predictor for therapy response monitoring and tumor staging over Response Evaluation Criteria In Solid Tumors (RECIST) or World Health Organization (WHO) criteria. In this study, the accuracy of subcutaneous rodent tumor volumes using preclinical magnetic resonance imaging (MRI), micro-computed tomography (micro-CT) and ultrasound (US) equipment and with an external caliper was compared using in-air micro-CT image volume of excised tumors determined as reference tumor volume in our prior study. Methods: MR, US and micro-CT images of subcutaneous SCC4 head and neck tumor xenografts were acquired 4, 6, 9, 11 and 13 days after tumor cell inoculation. Before MR and US scans, caliper measurements were made. After tumors were excised, in-air micro-CT imaging and ex vivo caliper measurements were performed. Tumor volumes were calculated using formula V = (π/6)*a*b*c where a, b and c are the maximum diameters in three perpendicular dimensions determined by the three image modalities and caliper, and compared with reference tumor volume by linear regression analysis as well as Bland-Altman plots. A one-way Analysis of Variance (ANOVA) test was also performed to compare volumes among caliper measurements. Results: The correlation coefficients (R2) of the regression lines for tumor volumes measured by the three imaging modalities and caliper were 0.9939, 0.9669, 0.9806, 0.9274, 0.9619 and 0.9819 for MRI, US and micro-CT, caliperbeforeMRI, caliperbeforeUS and ex vivo caliper respectively. In Bland-Altman plots, the average of tumor volume difference from reference tumor volume (bias) was significant for caliper and micro- CT, but not for MRI and US. Comparison of caliper measurements showed a significant difference (p < 0.05). Conclusion: Using the in-air micro-CT image volume, tumor volume measured by MRI was the most accurate among the three imaging modalities. In vivo caliper volume measurements showed unreliability while ex vivo caliper measurements reduced errors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Design and demonstration of a low‐field magnetic resonance imaging rhizotron for in‐field imaging of energy sorghum roots

Abstract Root phenotyping provides critical information to plant breeders for developing varieties with improved drought tolerance, greater root biomass, and greater nutrient use efficiency. Phenotyping roots in the natural environment is important for understanding the effect of the soil environment on root genotypic expressions. The goal of this work was to design and test a field‐scale mobile low‐field magnetic resonance imaging (LF‐MRI) Rhizotron that produces actionable root phenotyping data. We demonstrated this novel technology for root visualization and quantification using a LF‐MRI Rhizotron operating at 47 mT with two soil types. The LF‐MRI Rhizotron weights 453 kg, with a height of 90 cm, a diameter of 28 cm and an imaging field of view of 28 cm × 28 cm. The unit was operated in a Belk clay (Entic Hapluderts) and Weswood silt loam (Udifluventic Halustepts) generating 2‐D and 3‐D image data sets. The 2‐D image data had a collection time of 16.5 min per image at an image resolution of 2.2 mm per pixel. The 3‐D data had a collection time of 13 h per image with a 2.2 × 2.2 × 2.2 mm voxel resolution. Low‐field magnetic resonance imaging worked well for visualizing roots in moderate to high clay soils, demonstrating the potential for this technology; however, the broad application of this platform is hampered due to the prohibitively long scanning time to obtain 3‐D images. By increasing the field strength, and therefore the signal‐to‐noise ratio, faster scan times can enable a more useful system for root phenotyping.

Bagnall, G. Cody↗
DOE OSTI2019

Comparison of image noise and image quality between full-dose abdominal computed tomography scans reconstructed with weighted filtered back projection and half-dose scans reconstructed with improved sinogram-affirmed iterative reconstruction (SAFIRE*)

Purpose: To retrospectively compare the image noise, signal-to-noise ratio (SNR), and subjective image quality between CT images acquired with a dual-source, split-dose imaging protocol reconstructed at full and half doses with weighted filtered back projection (wFBP) and an improved sinogram-affirmed iterative reconstruction algorithm (SAFIRE*). Methods: Fifty-three consecutive patients underwent contrast-enhanced CT of the abdomen using a standardized dual-source, single energy CT protocol. Half-dose images were retrospectively generated using data from one detector only. Full-dose datasets were reconstructed with wFBP, while half-dose datasets were reconstructed with wFBP and SAFIRE* strengths 1–5. Region of interest analysis was performed to assess SNR and noise. Diagnostic acceptability, subjective noise, and spatial resolution were graded on a 10-point scale by two readers. Statistical analysis was carried out with repeated measures analysis of variance, Wilcoxon signed rank test, and Cohen’s κ test. Results: With the increasing strengths of SAFIRE*, a progressive reduction in noise and increase in SNR (p < 0.01) was observed. There was a statistically significant decrease in objective noise and increase in SNR in half-dose SAFIRE* strength 4 and 5 reconstructions compared to full-dose reconstructions using wFBP (p < 0.01). Qualitative analysis revealed a progressive increase in diagnostic acceptability, decrease in subjective noise and increase in spatial resolution for half-dose images reconstructed with the increasing strengths of SAFIRE* (p < 0.01). Conclusions: Half-dose CT images reconstructed with SAFIRE* at strength 4 and 5 have superior image quality compared to full-dose images reconstructed with wFBP. SAFIRE* potentially allows dose reductions in the order of 50% over wFBP.

62 RADIOLOGY AND NUCLEAR MEDICINE↗