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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

GRinding Automated Classification Engine

This work is an ML-driven framework for automated surface analysis of microscopy images. We create a training dataset by imaging stainless steel samples to benchmark four developed deep neural network architectures. These models, based on a YOLOv8n-cls backend, integrate image features and process metadata using various fusion methods to distinguish between acceptable and unacceptable surface finishes. This code is associated with publication "Classifying Alloy Surface Preparation Quality with Metadata-Infused Machine Learning for Rapid Alloy Discovery" for project APEX LDRD-ER (25-ERD-039)

Gongora, AldairE [Lawrence Livermore National Labo↗
DOE OSTI2012

Science Campaign-1 Pulsed Power Efforts [Slides]

The PHELIX portable pulsed-power driver is discussed. It is composed of two air-insulated, single Marx modules capable of storing 300 kJ of electrical energy. The Marx are cable coupled to a toroidal transformer with a 4:1 winding ratio. The experimental load is located at the center of the transformer. The components are mounted in a 8’x10’x18’ boxcar which can be moved in and out of the beam line at the LANL proton radiography facility and prevents EMI within the facility. PHELIX has successfully completed two liner implosion experiments with full diagnostic return from flash X-ray imaging, optical Faraday load current, and multi-channel PDV. Computational modeling with both the legacy 1D MHD code RAVEN and the LANL ASC-LAP FLAG code show good agreement with data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Nuclear Technology Research and Development (NTRD) Technical Monthly February FY18

[LANL] Energy-resolved neutron imaging data on transmutation fuels (Figure 1A) containing Am and Np were reanalyzed. The analysis using the SAMMY code was focused on retrieving absolute densities for five isotopes, 238U, 239Pu, 240Pu, 241Am and 237Np. The bulk composition described by partial densities of the main isotopes 237Np, 239Pu, 240Pu, and 242Am, resultant from the initial analysis agreed to better than 0.1 g/cc with the partial densities determined by mass spectrometry, except for 238U, which was overestimated by the initial approach. It was found that due to only a single resonance of 238U present in the fitted energy range of 1eV to 9eV (Figure 1 B), the refined areal densities for 238U were statistically insignificant, resulting in large errors. Consequently, the fitted energy range was extended to 24eV to include a second 238U resonance (Figure 1C, D), which stabilized the 238U areal densities, providing excellent agreement for all five isotopes. (A. Losko and S. Vogel)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

CALIBRATED ULTRA FAST IMAGE SIMULATIONS FOR THE DARK ENERGY SURVEY

Image simulations are becoming increasingly important in understanding the measurement process of the shapes of galaxies for weak lensing and the associated systematic effects. For this purpose we present the first implementation of the Monte Carlo Control Loops (MCCL), a coherent framework for studying systematic effects in weak lensing. It allows us to model and calibrate the shear measurement process using image simulations from the Ultra Fast Image Generator (UFig) and the image analysis software SExtractor. We apply this framework to a subset of the data taken during the Science Verification period (SV) of the Dark Energy Survey (DES). We calibrate the UFig simulations to be statistically consistent with one of the SV images, which covers ∼0.5 square degrees. We then perform tolerance analyses by perturbing six simulation parameters and study their impact on the shear measurement at the one-point level. This allows us to determine the relative importance of different parameters. For spatially constant systematic errors and point-spread function, the calibration of the simulation reaches the weak lensing precision needed for the DES SV survey area. Furthermore, we find a sensitivity of the shear measurement to the intrinsic ellipticity distribution, and an interplay between the magnitude-size and the pixel value diagnostics in constraining the noise model. This work is the first application of the MCCL framework to data and shows how it can be used to methodically study the impact of systematics on the cosmic shear measurement.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The molecular baryon cycle of M82

Baryons cycle into galaxies from the intergalactic medium and are converted into stars; a fraction of the baryons are ejected out of galaxies by stellar feedback. Here we present new high-resolution (3.″9; 68 pc) {sup 12}CO(2–1) and {sup 12}CO(3–2) images that probe these three stages of the baryon cycle in the nearby starburst M82. We combine these new observations with previous {sup 12}CO(1–0) and [Fe ii] images to study the physical conditions within the molecular gas. Using a Bayesian analysis and the radiative transfer code RADEX, we model temperatures and densities of molecular hydrogen, as well as column densities of CO. Besides the disk, we concentrate on two regions within the galaxy: an expanding super-bubble and the base of a molecular streamer. Shock diagnostics, kinematics, and optical extinction suggest that the streamer is an inflowing filament, with a mass inflow rate of molecular gas of 3.5 M{sub ⊙} yr{sup −1}. We measure the mass outflow rate of molecular gas of the expanding super-bubble to be 17 M{sub ⊙} yr{sup −1}, five times higher than the inferred inflow rate and 1.3 times the star formation rate of the galaxy. The high mass outflow rate and large star formation rate will deplete the galaxy of molecular gas within eight million years, unless there are additional sources of molecular gas.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

SU-E-T-02: 90Y Microspheres Dosimetry Calculation with Voxel-S-Value Method: A Simple Use in the Clinic

Purpose: To present a simple and feasible method of voxel-S-value (VSV) dosimetry calculation for daily clinical use in radioembolization (RE) with {sup 90}Y microspheres. Dose distributions are obtained and visualized over CT images. Methods: Spatial dose distributions and dose in liver and tumor are calculated for RE patients treated with Sirtex Medical miscrospheres at our center. Data obtained from the previous simulation of treatment were the basis for calculations: Tc-99m maggregated albumin SPECT-CT study in a gammacamera (Infinia, General Electric Healthcare.). Attenuation correction and ordered-subsets expectation maximization (OSEM) algorithm were applied.For VSV calculations, both SPECT and CT were exported from the gammacamera workstation and registered with the radiotherapy treatment planning system (Eclipse, Varian Medical systems). Convolution of activity matrix and local dose deposition kernel (S values) was implemented with an in-house developed software based on Python code. The kernel was downloaded from www.medphys.it. Final dose distribution was evaluated with the free software Dicompyler. Results: Liver mean dose is consistent with Partition method calculations (accepted as a good standard). Tumor dose has not been evaluated due to the high dependence on its contouring. Small lesion size, hot spots in health tissue and blurred limits can affect a lot the dose distribution in tumors. Extra work includes: export and import of images and other dicom files, create and calculate a dummy plan of external radiotherapy, convolution calculation and evaluation of the dose distribution with dicompyler. Total time spent is less than 2 hours. Conclusion: VSV calculations do not require any extra appointment or any uncomfortable process for patient. The total process is short enough to carry it out the same day of simulation and to contribute to prescription decisions prior to treatment. Three-dimensional dose knowledge provides much more information than other methods of dose calculation usually applied in the clinic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-53: A 3D Printed Phantom for the Use of Daily Quality Assurance Alignment Tests

Purpose: To discuss experiences and results for a 3D printed QA phantom used for daily alignment purposes for a six degrees-of-freedom (6DoF) table Methods: A 3D model was created using a fused deposition modeling (FDM) printer using free online computer-aided design (CAD) software. The model has been under use for daily QA alignment tests for a 6DoF couch. An aligned and angled baseplate were also printed in order to introduce known angles for 6DoF corrections during image-guidance. Unique registration contours were created on the faces of the phantom in order to achieve a better cone-beam computed tomography (CBCT) match using an auto-registration algorithm. A BB was also introduced at the center of the phantom in order to deliver an integrated daily Winston-Lutz (WL) test. Translational, rotational, and WL results were tabulated over one month. Results: The ’honeycomb’ structure of the print was apparent in the EPID images for the WL test, which affected the results of the analysis software. This was fixed by inserting a cube made of polyoxymethylene within the 3D phantom that encompass the BB. Auto-registration results for the three translational and three rotational from a known offset to the BB isocenter consistently fell within 1 mm and 0.2°, respectively. WL tests resulted in an average of 0.71 ± 0.14 mm. Conclusion: 3D printed models allow for accurate builds that can be customized to a variety of clinical needs. Results from translational, rotational, and WL show consistent results over a month’s time. Given its relatively cheap and streamlined workflow, 3D printing could be implemented into any clinic looking to create customized phantoms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Three-dimensional tomographic imaging for dynamic radiation behavior study using infrared imaging video bolometers in large helical device plasma

A three-dimensional (3D) tomography system using four InfraRed imaging Video Bolometers (IRVBs) has been designed with a helical periodicity assumption for the purpose of plasma radiation measurement in the large helical device. For the spatial inversion of large sized arrays, the system has been numerically and experimentally examined using the Tikhonov regularization with the criterion of minimum generalized cross validation, which is the standard solver of inverse problems. The 3D transport code EMC3-EIRENE for impurity behavior and related radiation has been used to produce phantoms for numerical tests, and the relative calibration of the IRVB images has been carried out with a simple function model of the decaying plasma in a radiation collapse. The tomography system can respond to temporal changes in the plasma profile and identify the 3D dynamic behavior of radiation, such as the radiation enhancement that starts from the inboard side of the torus, during the radiation collapse. The reconstruction results are also consistent with the output signals of a resistive bolometer. These results indicate that the designed 3D tomography system is available for the 3D imaging of radiation. The first 3D direct tomographic measurement of a magnetically confined plasma has been achieved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Metallic artifact mitigation and organ-constrained tissue assignment for Monte Carlo calculations of permanent implant lung brachytherapy

Purpose: To investigate methods of generating accurate patient-specific computational phantoms for the Monte Carlo calculation of lung brachytherapy patient dose distributions. Methods: Four metallic artifact mitigation methods are applied to six lung brachytherapy patient computed tomography (CT) images: simple threshold replacement (STR) identifies high CT values in the vicinity of the seeds and replaces them with estimated true values; fan beam virtual sinogram replaces artifact-affected values in a virtual sinogram and performs a filtered back-projection to generate a corrected image; 3D median filter replaces voxel values that differ from the median value in a region of interest surrounding the voxel and then applies a second filter to reduce noise; and a combination of fan beam virtual sinogram and STR. Computational phantoms are generated from artifact-corrected and uncorrected images using several tissue assignment schemes: both lung-contour constrained and unconstrained global schemes are considered. Voxel mass densities are assigned based on voxel CT number or using the nominal tissue mass densities. Dose distributions are calculated using the EGSnrc user-code BrachyDose for{sup 125}I, {sup 103}Pd, and {sup 131}Cs seeds and are compared directly as well as through dose volume histograms and dose metrics for target volumes surrounding surgical sutures. Results: Metallic artifact mitigation techniques vary in ability to reduce artifacts while preserving tissue detail. Notably, images corrected with the fan beam virtual sinogram have reduced artifacts but residual artifacts near sources remain requiring additional use of STR; the 3D median filter removes artifacts but simultaneously removes detail in lung and bone. Doses vary considerably between computational phantoms with the largest differences arising from artifact-affected voxels assigned to bone in the vicinity of the seeds. Consequently, when metallic artifact reduction and constrained tissue assignment within lung contours are employed in generated phantoms, this erroneous assignment is reduced, generally resulting in higher doses. Lung-constrained tissue assignment also results in increased doses in regions of interest due to a reduction in the erroneous assignment of adipose to voxels within lung contours. Differences in dose metrics calculated for different computational phantoms are sensitive to radionuclide photon spectra with the largest differences for{sup 103}Pd seeds and smallest but still considerable differences for {sup 131}Cs seeds. Conclusions: Despite producing differences in CT images, dose metrics calculated using the STR, fan beam + STR, and 3D median filter techniques produce similar dose metrics. Results suggest that the accuracy of dose distributions for permanent implant lung brachytherapy is improved by applying lung-constrained tissue assignment schemes to metallic artifact corrected images.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Technical Note: A fast online adaptive replanning method for VMAT using flattening filter free beams

Purpose: To develop a fast replanning algorithm based on segment aperture morphing (SAM) for online replanning of volumetric modulated arc therapy (VMAT) with flattening filter free (FFF) beams. Methods: A software tool was developed to interface with a VMAT research planning system, which enables the input and output of beam and machine parameters of VMAT plans. The SAM algorithm was used to modify multileaf collimator positions for each segment aperture based on the changes of the target from the planning (CT/MR) to daily image [CT/CBCT/magnetic resonance imaging (MRI)]. The leaf travel distance was controlled for large shifts to prevent the increase of VMAT delivery time. The SAM algorithm was tested for 11 patient cases including prostate, pancreatic, and lung cancers. For each daily image set, three types of VMAT plans, image-guided radiation therapy (IGRT) repositioning, SAM adaptive, and full-scope reoptimization plans, were generated and compared. Results: The SAM adaptive plans were found to have improved the plan quality in target and/or critical organs when compared to the IGRT repositioning plans and were comparable to the reoptimization plans based on the data of planning target volume (PTV)-V100 (volume covered by 100% of prescription dose). For the cases studied, the average PTV-V100 was 98.85% ± 1.13%, 97.61% ± 1.45%, and 92.84% ± 1.61% with FFF beams for the reoptimization, SAM adaptive, and repositioning plans, respectively. The execution of the SAM algorithm takes less than 10 s using 16-CPU (2.6 GHz dual core) hardware. Conclusions: The SAM algorithm can generate adaptive VMAT plans using FFF beams with comparable plan qualities as those from the full-scope reoptimization plans based on daily CT/CBCT/MRI and can be used for online replanning to address interfractional variations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

YNOGK: A NEW PUBLIC CODE FOR CALCULATING NULL GEODESICS IN THE KERR SPACETIME

Following the work of Dexter and Agol, we present a new public code for the fast calculation of null geodesics in the Kerr spacetime. Using Weierstrass's and Jacobi's elliptic functions, we express all coordinates and affine parameters as analytical and numerical functions of a parameter p, which is an integral value along the geodesic. This is the main difference between our code and previous similar ones. The advantage of this treatment is that the information about the turning points does not need to be specified in advance by the user, and many applications such as imaging, the calculation of line profiles, and the observer-emitter problem, become root-finding problems. All elliptic integrations are computed by Carlson's elliptic integral method as in Dexter and Agol, which guarantees the fast computational speed of our code. The formulae to compute the constants of motion given by Cunningham and Bardeen have been extended, which allow one to readily handle situations in which the emitter or the observer has an arbitrary distance from, and motion state with respect to, the central compact object. The validation of the code has been extensively tested through applications to toy problems from the literature. The source FORTRAN code is freely available for download on our Web site http://www1.ynao.ac.cn/{approx}yangxl/yxl.html.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

TU-H-BRA-04: A Novel Superconducting Magnet Design for Optimized Patient Access and Minimal SSD for Use in a Linac-MR Hybrid

Purpose: A prototype rotating hybrid MR imaging system and linac has been developed to allow for simultaneous imaging and radiation delivery parallel to B{sub 0}. However, the design of a compact magnet capable of rotation in a small vault with sufficient patient access and a typical clinical source-to-surface distance (SSD) is challenging. This work presents a novel superconducting magnet design that allows for a reduced SSD and ample patient access by moving the superconducting coils to the side of the yoke. The yoke and pole-plate structures are shaped to direct the magnetic flux appropriately. Methods: The surface of the pole plate for the magnet assembly is optimized. The magnetic field calculations required in this work are performed with the 3D finite element method software package Opera-3D. Each tentative design strategy is virtually modeled in this software package and externally controlled by MATLAB, with its key geometries defined as variables. The particle swarm optimization algorithm is used to optimize the variables subject to the minimization of a cost function. At each iteration, Opera-3D will solve the magnetic field solution over a field-of-view suitable for MR imaging and the degree of field uniformity will be assessed to calculate the value of the cost function associated with that iteration. Results: An optimized magnet assembly that generates a homogenous 0.2T magnetic field over an ellipsoid with large axis of 30 cm and small axes of 20 cm is obtained. Conclusion: The distinct features of this model are the minimal distance between the yoke’s top and the isocentre and the improved patient access. On the other hand, having homogeneity over an ellipsoid give us a larger field-of-view, essential for geometric accuracy of the MRI system. The increase of B{sub 0} from 0.2T in the present model to 0.5T is the subject of future work. Funding Sources: Alberta Innovates - Health Solutions (AIHS)| Disclosure and Conflict of Interest: B. Gino Fallone is a co-founder and CEO of MagnetTx Oncology Solutions (under discussions to license Alberta biplanar linac MR for commercialization).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-138: On the Ion Beam Range and Dose Verification in Hadron Therapy Using Sound Waves

Purpose: Accurate range verification is of great importance to fully exploit the potential benefits of ion beam therapies. Current research efforts on this topic include the use of PET imaging of induced activity, detection of emerging prompt gamma rays or secondary particles. It has also been suggested recently to detect the ultrasound waves emitted through the ion energy absorption process. The energy absorbed in a medium is dissipated as heat, followed by thermal expansion that leads to generation of acoustic waves. By using an array of ultrasound transducers the precise spatial location of the Bragg peak can be obtained. The shape and intensity of the emitted ultrasound pulse depend on several variables including the absorbed energy and the pulse length. The main objective of this work is to understand how the ultrasound wave amplitude and shape depend on the initial ion energy and intensity. This would help guide future experiments in ionoacoustic imaging. Methods: The absorbed energy density for protons and carbon ions of different energy and field sizes were obtained using Fluka Monte Carlo code. Subsequently, the system of coupled equations for temperature and pressure is solved for different ion pulse intensities and lengths to obtain the pressure wave shape, amplitude and spectral distribution. Results: The proposed calculations show that the excited pressure wave amplitude is proportional to the absorbed energy density and for longer ion pulses inversely proportional to the ion pulse duration. It is also shown that the resulting ionoacoustic pressure distribution depends on both ion pulse duration and time between the pulses. Conclusion: The Bragg peak localization using ionoacoustic signal may eventually lead to the development of an alternative imaging method with sub-millimeter resolution. It may also open a way for in-vivo dose verification from the measured acoustic signal.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Phase Imaging: A Compressive Sensing Approach

Since Wolfgang Pauli posed the question in 1933, whether the probability densities |Ψ(r)|² (real-space image) and |Ψ(q)|² (reciprocal space image) uniquely determine the wave function Ψ(r) [1], the so called Pauli Problem sparked numerous methods in all fields of microscopy [2, 3]. Reconstructing the complete wave function Ψ(r) = a(r)e-iφ(r) with the amplitude a(r) and the phase φ(r) from the recorded intensity enables the possibility to directly study the electric and magnetic properties of the sample through the phase. In transmission electron microscopy (TEM), electron holography is by far the most established method for phase reconstruction [4]. Requiring a high stability of the microscope, next to the installation of a biprism in the TEM, holography cannot be applied to any microscope straightforwardly. Recently, a phase retrieval approach was proposed using conventional TEM electron diffractive imaging (EDI). Using the SAD aperture as reciprocal-space constraint, a localized sample structure can be reconstructed from its diffraction pattern and a real-space image using the hybrid input-output algorithm [5]. We present an alternative approach using compressive phase-retrieval [6]. Our approach does not require a real-space image. Instead, random complimentary pairs of checkerboard masks are cut into a 200 nm Pt foil covering a conventional TEM aperture (cf. Figure 1). Used as SAD aperture, subsequently diffraction patterns are recorded from the same sample area. Hereby every mask blocks different parts of gold particles on a carbon support (cf. Figure 2). The compressive sensing problem has the following formulation. First, we note that the complex-valued reciprocal-space wave-function is the Fourier transform of the (also complex-valued) real-space wave-function, Ψ(q) = F[Ψ(r)], and subsequently the diffraction pattern image is given by |Ψ(q)|2 = |F[Ψ(r)]|2. We want to find Ψ(r) given a few differently coded diffraction pattern measurements yn = |F[HnΨ(r)]|2, where the matrices Hn encode the mask structure of the aperture. This is a nonlinear inverse problem, but has been shown to be solvable even in the underdetermined case [6]. Since each diffraction pattern yn contains diffraction information from selected regions of the same sample, the differences in each pattern contain local phase information, which can be combined to form a full estimate of the real-space wave-function[7]. References: [1] W. Pauli in “Die allgemeinen Prinzipien der Wellenmechanik“, ed. H Geiger and W Scheel, (Julius Springer, Berlin). [2] A. Tonomura, Rev. Mod. Phys. 59 (1987), p. 639. [3] J. Miao et al, Nature 400 (1999), p. 342. [4] H. Lichte et al, Annu. Rev. Mater. Res. 37 (2007), p. 539. [5] J. Yamasaki et al, Appl. Phys. Lett. 101 (2012), 234105. [6] P Schniter and S Rangan. Signal Proc., IEEE Trans. on. 64(4), (2015), pp. 1043. [7] Supported by the Chemical Imaging, Signature Discovery, and Analytics in Motion initiatives at PNNL. PNNL is operated by Battelle Memorial Inst. for the US DOE; contract DE-AC05-76RL01830.

Schneider, Sebastian↗
DOE OSTI2020

Detect and correct bias in multi-site neuroimaging datasets

The desire to train complex machine learning algorithms and to increase the statistical power in association studies drives neuroimaging research to use ever-larger datasets. The most obvious way to increase sample size is by pooling scans from independent studies. However, simple pooling is often ill-advised as selection, measurement, and confounding biases may creep in and yield spurious correlations. In this work, we combine 35,320 magnetic resonance images of the brain from 17 studies to examine bias in neuroimaging. In the first experiment, Name That Dataset, we provide empirical evidence for the presence of bias by showing that scans can be correctly assigned to their respective dataset with 71.5% accuracy. Given such evidence, we take a closer look at confounding bias, which is often viewed as the main shortcoming in observational studies. In practice, we neither know all potential confounders nor do we have data on them. Hence, we model confounders as unknown, latent variables. Kolmogorov complexity is then used to decide whether the confounded or the causal model provides the simplest factorization of the graphical model. Finally, we present methods for dataset harmonization and study their ability to remove bias in imaging features. In particular, we propose an extension of the recently introduced ComBat algorithm to control for global variation across image features, inspired by adjusting for unknown population stratification in genetics. Overall, our results demonstrate that harmonization can reduce dataset-specific information in image features. Further, confounding bias can be reduced and even turned into a causal relationship. However, harmonization also requires caution as it can easily remove relevant subject-specific information. Code is available at https://github.com/ai-med/Dataset-Bias.

42 ENGINEERING↗
DOE OSTI2025

Comparison of laser-produced plasma spatio-temporal electron density evolution measured using interferometry with simulation results

Due to the difficulties associated with experimental measurements of laser-produced plasma (LPP) properties during the earliest stages of plasma evolution, radiation hydrodynamic codes are often used. However, although these codes have been extensively validated in the higher intensity regimes, validation at low to moderate intensities has been limited. In this study, the spatio-temporal electron density evolution in an LPP generated at moderate laser intensities and at various laser wavelengths was validated against the FLASH code for times up to 20 ns. The LPP was generated by focusing the fundamental and various harmonics radiation (1064, 532, and 266 nm) from a 6 ns full width half maximum Nd:YAG laser, at a laser intensity of 10 GW cm -2 , onto a copper target. The spatio-temporal density evolution of the expanding plasma was analyzed using Nomarski interferometry. Experimental measurements were found to be consistent with FLASH simulations, and the dependence of electron densities on wavelength was found to be in agreement with analytical models, varying as n e ∝ λ -0.7 . However, slight differences were noted in the widths and shape functions of the experimental and simulated electron density profiles.

2D fast imaging↗
DOE OSTI2016

SU-F-R-13: Decoding 18F-FDG Uptake Heterogeneity for Primary and Lymphoma Tumors by Using Texture Analysis in PET Images

Purpose: To explore 18F-FDG uptake heterogeneity of primary tumor and lymphoma tumor by texture features of PET image and quantify the heterogeneity difference between primary tumor and lymphoma tumor. Methods: 18 patients with primary tumor and lymphoma tumor in lung cancer were enrolled. All patients underwent whole-body 18F-FDG PET/CT scans before treatment. Texture features, based on Gray-level Co-occurrence Matrix, second and high order matrices are extracted from code using MATLAB software to quantify 18F-FDG uptake heterogeneity. The relationships of volume between energy, entropy, correlation, homogeneity and contrast were analyzed. Results: For different cases, tumor heterogeneity was not the same. Texture parameters (contrast, entropy, and correlation) of lymphoma were lower than primary tumor. On the contrast, the texture parameters (energy, homogeneity and inverse different moment) of lymphoma were higher than primary tumor. Significantly, correlations were observed between volume and energy (primary, r=−0.194, p=0.441; lymphoma, r=−0.339, p=0.582), homogeneity (primary, r=−0.146, p=0.382; lymphoma, r=−0.193, p=0.44), inverse difference moment (primary, r=−0.14, p=0.374; lymphoma, r=−0.172, p=0.414) and a positive correlation between volume and entropy (primary, r=0.233, p=0.483; lymphoma, r=0.462, p=0.680), contrast (primary, r=0.159, p=0.399; lymphoma, r=0.341, p=0.584), correlation (primary, r=0.027, p=0.165; lymphoma, r=0.046, p=0.215). For the same patient, energy for primary and lymphoma tumor is equal. The volume of lymphoma is smaller than primary tumor, but the homogeneity were higher than primary tumor. Conclusion: This study showed that there were effective heterogeneity differences between primary and lymphoma tumor by FDG-PET image texture analysis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Automated Programmable Logic Controller Memory Forensics Using RGB Image Analysis and Deep Learning

The introduction of Industry 4.0 and Internet-based technologies has enhanced industrial control system operations but have inadvertently increased their vulnerabilities to cyber attacks. When an industrial control system is compromised, security analysts need to identify the root cause quickly to start the recovery process and develop mitigation strategies. Memory forensics is critical in the incident analysis process to ascertain what occurred. Approaches for analyzing the persistent memory in industrial control devices are limited and almost nonexistent for volatile memory. This chapter proposes an automated methodology for programmable logic controller memory dump analysis using computer vision and deep learning techniques. The methodology converts the sequences of bytes in a programmable logic controller memory dump to red-green-blue pixels and employs a deep learning model that learns the underlying patterns and features of pre-labeled forensic artifacts in images and segments them into distinct regions. The trained model is employed to automatically segment new memory images and identify forensic artifacts. Evaluation of the methodology on a Schneider Electric Modicon M221 programmable logic controller under code injection and code modification attacks demonstrates its ability to detect attack artifacts in memory dumps.

Asmar Awad, Rima [ORNL] (ORCID:0000000233407742)↗