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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Parallel algorithm for determining motion vectors in ice floe images by matching edge features

A parallel algorithm is described to determine motion vectors of ice floes using time sequences of images of the Arctic ocean obtained from the Synthetic Aperture Radar (SAR) instrument flown on-board the SEASAT spacecraft. Researchers describe a parallel algorithm which is implemented on the MPP for locating corresponding objects based on their translationally and rotationally invariant features. The algorithm first approximates the edges in the images by polygons or sets of connected straight-line segments. Each such edge structure is then reduced to a seed point. Associated with each seed point are the descriptions (lengths, orientations and sequence numbers) of the lines constituting the corresponding edge structure. A parallel matching algorithm is used to match packed arrays of such descriptions to identify corresponding seed points in the two images. The matching algorithm is designed such that fragmentation and merging of ice floes are taken into account by accepting partial matches. The technique has been demonstrated to work on synthetic test patterns and real image pairs from SEASAT in times ranging from .5 to 0.7 seconds for 128 x 128 images.

Manohar, M.↗
DOE OSTI2014

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.

3D electron microscopy↗
DOE OSTI2016

Poster - 32: Atlas Selection for Automated Segmentation of Pelvic CT for Prostate Radiotherapy

Atlas based-segmentation has recently been evaluated for use in prostate radiotherapy. In a typical approach, the essential step is the selection of an atlas from a database that the best matches of the target image. This work proposes an atlas selection strategy and evaluate it impacts on final segmentation accuracy. Several anatomical parameters were measured to indicate the overall prostate and body shape, all of these measurements obtained on CT images. A brute force procedure was first performed for a training dataset of 20 patients using image registration to pair subject with similar contours; each subject was served as a target image to which all reaming 19 images were affinity registered. The overlap between the prostate and femoral heads was quantified for each pair using the Dice Similarity Coefficient (DSC). Finally, an atlas selection procedure was designed; relying on the computation of a similarity score defined as a weighted sum of differences between the target and atlas subject anatomical measurement. The algorithm ability to predict the most similar atlas was excellent, achieving mean DSCs of 0.78 ± 0.07 and 0.90 ± 0.02 for the CTV and either femoral head. The proposed atlas selection yielded 0.72 ± 0.11 and 0.87 ± 0.03 for CTV and either femoral head. The DSC obtained with the proposed selection method were slightly lower than the maximum established using brute force, but this does not include potential improvements expected with deformable registration. The proposed atlas selection method provides reasonable segmentation accuracy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Poster — Thur Eve — 59: Atlas Selection for Automated Segmentation of Pelvic CT for Prostate Radiotherapy

Automated atlas-based segmentation has recently been evaluated for use in planning prostate cancer radiotherapy. In the typical approach, the essential step is the selection of an atlas from a database that best matches the target image. This work proposes an atlas selection strategy and evaluates its impact on the final segmentation accuracy. Prostate length (PL), right femoral head diameter (RFHD), and left femoral head diameter (LFHD) were measured in CT images of 20 patients. Each subject was then taken as the target image to which all remaining 19 images were affinely registered. For each pair of registered images, the overlap between prostate and femoral head contours was quantified using the Dice Similarity Coefficient (DSC). Finally, we designed an atlas selection strategy that computed the ratio of PL (prostate segmentation), RFHD (right femur segmentation), and LFHD (left femur segmentation) between the target subject and each subject in the atlas database. Five atlas subjects yielding ratios nearest to one were then selected for further analysis. RFHD and LFHD were excellent parameters for atlas selection, achieving a mean femoral head DSC of 0.82 ± 0.06. PL had a moderate ability to select the most similar prostate, with a mean DSC of 0.63 ± 0.18. The DSC obtained with the proposed selection method were slightly lower than the maximums established using brute force, but this does not include potential improvements expected with deformable registration. Atlas selection based on PL for prostate and femoral diameter for femoral heads provides reasonable segmentation accuracy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Quant-CT: Segmenting and Quantifying Computed Tomography

Quant-CT is currently a plugin to ImageJ, designed as a Java-class that provides control mechanism for the user to choose volumes of interest within porous material, followed by the selection of image subsamples for automated tuning of parameters for filters and classifiers, and finally measurement of material geometry, porosity, and visualization. Denoising is mandatory before any image interpretation, and we implemented a new 3D java code that performs bilateral filtering of data. Segmentation of the dense material is essential before any quantifications about geological sample structure, and we invented new schemes to deal with over segmentation when using statistical region merging algorithm to pull out grains that compose imaged material. It make uses of ImageJ API and other standard and thirty-party APIs. Quant-CT conception started in 2011 under Scidac-e sponsor, and details of the first prototype were documented in publications below. While it is used right now for microtomography images, it can potentially be used by anybody with 3D image data obtained by experiment or produced by simulation.

Daniela Ushizima, Wes Bethel↗
DOE OSTI2019

Computed tomography-based texture analysis of bladder cancer: differentiating urothelial carcinoma from micropapillary carcinoma

Purpose: The purpose of the study is to determine the feasibility of using computed tomography-based texture analysis (CTTA) in differentiating between urothelial carcinomas (UC) of the bladder from micropapillary carcinomas (MPC) of the bladder. Methods: Regions of interests (ROIs) of computerized tomography (CT) images of 33 MPCs and 33 UCs were manually segmented and saved. Custom MATLAB code was used to extract voxel information corresponding to the ROI. The segmented tumors were input to a pre-existing radiomics platform with a CTTA panel. A total of 58 texture metrics were extracted using four different texture extraction techniques and statistically analyzed using a Wilcoxon rank-sum test to determine the differences between UCs and MPCs. Results: Of the 58 texture metrics extracted using the gray level co-occurrence matrix (GLCM) and gray level difference matrix (GLDM), 28 texture metrics were statistically significant (p < 0.05) for differences in tumor textures and 27 texture metrics were statistically significant (p < 0.05) for peritumoral fat textures. The remaining nine metrics extracted using histogram and fast Fourier transform analyses did not show significant differences between the textures of the tumors and their peritumoral fat. Conclusions: CTTA shows that MPC have a more heterogeneous texture compared to UC. As visual discrimination of MPC from UC from clinical CT scans are difficult, results from this study suggest that tumor heterogeneity extracted using GLCM and GLDM may be a good imaging aid in segregating MPC from UC. This tool can aid clinicians in further sub-classifying bladder cancers on routine imaging, a process which has potential to alter treatment and patient care.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2001

Use of Yohkoh SXT in Measuring the Net Current and CME Productivity of Active Regions

In our investigation of the correlation of global nonpotentiality of active regions to their CME productivity (Falconer, D.A. 2001, JGR, in press, and Falconer, Moore, & Gary, 2000, EOS 82, 20 S323), we use Yohkoh SXT images for two purposes. The first use is to help resolve the 180 degree ambiguity in the direction of the observed transverse magnetic field. Resolution of the 180 degree ambiguity is important, since the net current, one of our measures of global nonpotentiality, is derived from integrating the dot product of the transverse field around a contour (I(sub N)=(integral)BT(raised dot)dl). The ambiguity results from the observed transverse field being determined from the linear polarization, which gives the plane of the direction, but leaves a 180 degrees ambiguity. Automated methods to resolve the ambiguity ranging from the simple acute angle rule (Falconer, D.A. 2001) to the more sophisticated annealing method (Metcalf T.R. 1994). For many active regions, especially ones that are nearly potential these methods work well. But for very nonpotential active regions where the shear angle (the angle between the observed and potential transverse field) is near 90 degrees throughout large swaths along the main neutral line, both methods can resolve the ambiguity incorrectly for long segments of the neutral line. By determining from coronal images, such as those from Yohkoh/SXT, the sense of shear along the main neutral line in the active region, these cases can be identified and corrected by a modification of the acute angle rule described here. The second use of Yohkoh/SXT in this study is to check for the cusped coronal arcades of long-duration eruptive flares. This signature is an excellent proxy for CMEs, and was used by Canfield, Hudson, and McKenzie (1999 GRL V26, 6, 627-630). This work is funded by NSF through the Space Weather Program and by NASA through the Solar Physics Supporting Research and Technology Program.

Falconer, D. A.↗
DOE OSTI2014

MCTP system model based on linear programming optimization of apertures obtained from sequencing patient image data maps

Purpose: The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. Methods: The planning system (called CARMEN) is a full MC-TPS, controlled through aMATLAB interface, which is based on the sequencing of a novel map, called “biophysical” map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to calculate the beamlet dose in order to combine them with different weights during the optimization process. Results: Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a demanding dose-escalation; a partial breast irradiation case (Case II) solved with photon and electron modulated beams (IMRT + MERT); and a prostatic bed case (Case III) with a pronounced concave-shaped PTV by using volumetric modulated arc therapy. In the three cases, the required target prescription doses and constraints on organs at risk were fulfilled in a short enough time to allow routine clinical implementation. The quality assurance protocol followed to check CARMEN system showed a high agreement with the experimental measurements. Conclusions: A Monte Carlo treatment planning model exclusively based on maps performed from patient imaging data has been presented. The sequencing of these maps allows obtaining deliverable apertures which are weighted for modulation under a linear programming formulation. The model is able to solve complex radiotherapy treatments with high accuracy in an efficient computation time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

DETERMINATION OF HLW GLASS MELT RATE USING X-RAY COMPUTED TOMOGRAPHY

The purpose of the high-level waste (HLW) glass melt rate study is two-fold: (1) to gain a better understanding of the impact of feed chemistry on melt rate through bench-scale testing, and (2) to develop a predictive tool for melt rate in support of the on-going frit development efforts for the Defense Waste Processing Facility (DWPF). In particular, the focus is on predicting relative melt rates, not the absolute melt rates, of various HLW glass formulations solely based on feed chemistry, i.e., the chemistry of both waste and glass-forming frit for DWPF. Critical to the successful melt rate modeling is the accurate determination of the melting rates of various HLW glass formulations. The baseline procedure being used at the Savannah River National Laboratory (SRNL) is to; (1) heat a 4 inch-diameter stainless steel beaker containing a mixture of dried sludge and frit in a furnace for a preset period of time, (2) section the cooled beaker along its diameter, and (3) measure the average glass height across the sectioned face using a ruler. As illustrated in Figure 1-1, the glass height is measured for each of the 16 horizontal segments up to the red lines where relatively large-sized bubbles begin to appear. The linear melt rate (LMR) is determined as the average of all 16 glass height readings divided by the time during which the sample was kept in the furnace. This 'visual' method has proved useful in identifying melting accelerants such as alkalis and sulfate and further ranking the relative melt rates of candidate frits for a given sludge batch. However, one of the inherent technical difficulties of this method is to determine the glass height in the presence of numerous gas bubbles of varying sizes, which is prevalent especially for the higher-waste-loading glasses. That is, how the red lines are drawn in Figure 1-1 can be subjective and, therefore, may influence the resulting melt rates significantly. For example, if the red lines are drawn too low, a significant amount of glassy material interspersed among the gas bubbles will be excluded, thus underestimating the melt rate. Likewise, if they are drawn too high, many large voids will be counted as glass, thus overestimating the melt rate. As will be shown later in this report, there is also no guarantee that a given distribution of glass and gas bubbles along a particular sectioned plane will always be representative of the entire sample volume. Poor reproducibility seen in some LMR data may be related to these difficulties of the visual method. In addition, further improvement of the existing melt rate model requires that the overall impact of feed chemistry on melt rate be reflected on measured data at a greater quantitative resolution on a more consistent basis than the visual method can provide. An alternate method being pursued is X-ray computed tomography (CT). It involves X-ray scanning of glass samples, performing CT on the 2-D X-ray images to build 3-D volumetric data, and adaptive segmentation analysis of CT results to not only identify but quantify the distinct regions within each sample based on material density and morphologies. The main advantage of this new method is that it can determine the relative local density of the material remaining in the beaker after the heat treatment regardless of its morphological conditions by selectively excluding all the voids greater than a given volumetric pixel (voxel) size, thus eliminating much of the subjectivity involved in the visual method. As a result, the melt rate data obtained from CT scan will give quantitative descriptions not only on the fully-melted glass, but partially-melted and unmelted feed materials. Therefore, the CT data are presumed to be more reflective of the actual melt rate trends in continuously-fed melters than the visual data. In order to test the applicability of X-ray CT scan to the HLW glass melt rate study, several new series of HLW simulant/frit mixtures were melted in the Melt Rate Furnace (MRF) and the contents of each cooled but un-sectioned beaker were CT scanned and analyzed. For comparison purposes, a cross-sectional X-ray image of each sample was used to estimate the melt rate using the visual method. In order to see the impact of feed chemistry on melt rate more clearly, a total of ten frit-only glasses (i.e., no waste) were also made, CT scanned and analyzed. In addition, two historical glass series which were previously sectioned were re-joined and CT scanned; the results were then compared to the visual data obtained earlier. All the work performed on these historical samples will be documented separately in another report. This report describes the methodologies used to interpret and apply the results of X-ray CT scans to the HLW melt rate study and further highlights some of the key results on the compositional dependence of melt rate and the cross-comparison of the visual and CT results.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Quantifying the Impact of Charge Rate and Number of Cycles on Structural Degeneration of Li-Ion Battery Electrodes

A quantitative link between crack evolution in lithium-ion positive electrodes and the degrading performance on cells is not yet well established nor is any single technique capable of doing so widely available. Here, we demonstrate a widely accessible high-throughput approach to quantifying crack evolution within electrodes. The approach applies super-resolution scanning electron microscopy (SEM) imaging of cross-sectioned NMC532 electrodes, followed by segmentation and quantification of crack features. Crack properties such as crack intensity, crack width and length are quantified as a function of charge rate (1C, 6C, and 9C) and cycle number (25, 225, and 600 cycles). Hundreds of particles are characterized for statistical confidence in the quantitative crack measurements. The data on crack evolution is compared to electrochemical data from full cells and half cells with the NMC532 positive electrodes. We show that while crack evolution strongly correlates with capacity fade in the first 25 cycles, it does not correlate well for the following hundreds of cycles indicating that cracking may not be the dominant cause of capacity fade throughout the cycle-life of cells.

25 ENERGY STORAGE↗
DOE OSTI2023

The large-area hybrid-optics CLAS12 RICH: First years of data-taking

The CLAS12 deep-inelastic scattering experiment at the upgraded 12 GeV continuous electron beam accelerator facility of Jefferson Lab conjugates luminosity and wide acceptance to study the 3D nucleon structure in the yet poorly explored valence region, and to perform precision measurements in hadron spectroscopy. A large area ring-imaging Cherenkov detector has been designed to achieve the required hadron identification in the momentum range from 3 GeV/c to 8 GeV/c, with the kaon rate about one order of magnitude lower than the rate of pions and protons. The adopted solution comprises aerogel radiator and composite mirrors in a novel hybrid optics design, where either direct or reflected light could be imaged in a high-packed and high-segmented photon detector. The first RICH module was assembled during the second half of 2017 and installed at the beginning of January 2018, in time for the start of the experiment. The second RICH module, planned with the goal to be ready for the beginning of the operation with polarized targets, has been timely built despite the complications caused by the pandemic crisis and successfully installed in June 2022. Finally, the detector performance is here discussed with emphasis on the operation and stability during the data-taking, calibration and alignment procedures, reconstruction and pattern recognition algorithms, and particle identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Segmentation-free empirical beam hardening correction for CT

Purpose: The polychromatic nature of the x-ray beams and their effects on the reconstructed image are often disregarded during standard image reconstruction. This leads to cupping and beam hardening artifacts inside the reconstructed volume. To correct for a general cupping, methods like water precorrection exist. They correct the hardening of the spectrum during the penetration of the measured object only for the major tissue class. In contrast, more complex artifacts like streaks between dense objects need other techniques of correction. If using only the information of one single energy scan, there are two types of corrections. The first one is a physical approach. Thereby, artifacts can be reproduced and corrected within the original reconstruction by using assumptions in a polychromatic forward projector. These assumptions could be the used spectrum, the detector response, the physical attenuation and scatter properties of the intersected materials. A second method is an empirical approach, which does not rely on much prior knowledge. This so-called empirical beam hardening correction (EBHC) and the previously mentioned physical-based technique are both relying on a segmentation of the present tissues inside the patient. The difficulty thereby is that beam hardening by itself, scatter, and other effects, which diminish the image quality also disturb the correct tissue classification and thereby reduce the accuracy of the two known classes of correction techniques. The herein proposed method works similar to the empirical beam hardening correction but does not require a tissue segmentation and therefore shows improvements on image data, which are highly degraded by noise and artifacts. Furthermore, the new algorithm is designed in a way that no additional calibration or parameter fitting is needed. Methods: To overcome the segmentation of tissues, the authors propose a histogram deformation of their primary reconstructed CT image. This step is essential for the proposed algorithm to be segmentation-free (sf). This deformation leads to a nonlinear accentuation of higher CT-values. The original volume and the gray value deformed volume are monochromatically forward projected. The two projection sets are then monomially combined and reconstructed to generate sets of basis volumes which are used for correction. This is done by maximization of the image flatness due to adding additionally a weighted sum of these basis images. sfEBHC is evaluated on polychromatic simulations, phantom measurements, and patient data. The raw data sets were acquired by a dual source spiral CT scanner, a digital volume tomograph, and a dual source micro CT. Different phantom and patient data were used to illustrate the performance and wide range of usability of sfEBHC across different scanning scenarios. The artifact correction capabilities are compared to EBHC. Results: All investigated cases show equal or improved image quality compared to the standard EBHC approach. The artifact correction is capable of correcting beam hardening artifacts for different scan parameters and scan scenarios. Conclusions: sfEBHC generates beam hardening-reduced images and is furthermore capable of dealing with images which are affected by high noise and strong artifacts. The algorithm can be used to recover structures which are hardly visible inside the beam hardening-affected regions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRSDate not supplied

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was implemented to offer an efficient framework for determining material characteristics from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enable parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM). SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography or other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗
DOE OSTI2015

SU-E-T-16: A Comparison of Expected Dwell Times and Dose Variations for NAMD Patients Treated with An Episcleral Brachytherapy Device

Purpose: To evaluate the variations in dwell times and doses expected when using an episcleral brachytherapy device for treatment of neovascular agerelated macular degeneration (n-AMD) based on accurate imaging modalities Methods: Data from 40 eyes from 40 subjects with known n- AMD acquired through the Distance of Choroid Study (DOCS) conducted at Moorfields Eye Hospital was used to determine the target depth; the distance from the outer scleral surface of the eye, through the choroid, to the apex of the choroidal neovascularization (CNV). Each subject underwent, in triplicate, enhanced-depth Spectral Domain Optical Coherence Tomography (SD-OCT), Swept Source Optical Coherence Tomography, (SS-OCT) and Ocular Ultrasound (O-US). These data are the most comprehensive and accurate measurements of the dimensions of the CNV and adjacent layers of the eye for this cohort of patients. During treatment of n-AMD, patients receive a dose of 24Gy to the apex at the target depth. Using the percentage depth dose for a Sr-90 episcleral brachytherapy device, dwell times and doses to the apex were computed to determine the expected variations. Results: The mean target depth and the 95% confidence interval (CI) determined by combining O-US with SD-OCT were 1326 (956,1696)µm and with SS-OCT were 1332 (970,1693)µm. The calculated corresponding mean dwell times and 95% (CI) were 334 (223,445)s and 335 (226,445)s for SD-OCT and SS-OCT determined depths, respectively. The corresponding mean apex dose and 95% (CI) were 24 (35.9,18.0)Gy (SD-OCT) and 24 (35.6,18.1)Gy (SS-OCT). Conclusion: For episcleral brachytherapy treatment of n-AMD, using a patient population average target depth for treatment planning is inadequate, resulting in dose variations of a factor of approximately two over the 95% CI and larger variations for a nontrivial segment of the population. Each patient should have individualized imaging studies to determine the target depth for use in the dwell time calculation. Study was sponsored by Salutaris Medical Devices, Ltd., a subsidiary of Salutaris Medical Devices, Inc. Hamilton and Marsteller are founders of Salutaris Medical Devices, Inc. Drew, McGovern and Vitali are minor equity holders in Salutaris Medical Devices, Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

3D characterization of trans- and inter-lamellar fatigue crack in (α + β) Ti alloy

This paper presents a three dimensional image processing strategy that has been developed to quantitatively analyze and correlate the path of a fatigue crack with the lamellar microstructure found in Ti-6246. The analysis is carried out on X-ray microtomography images acquired in situ during uniaxial fatigue testing. The crack, the primary β-grain boundaries and the α lamellae have been segmented separately and merged for the first time to allow a better characterization and understanding of their mutual interaction. This has particularly emphasized the role of translamellar crack growth at a very high propagation angle with regard to the lamellar orientation, supporting the central role of colonies favorably oriented for basal 〈a〉 slip to guide the crack in the fully lamellar microstructure of Ti alloy. - Highlights: • 3D tomography images reveal strong short fatigue crack interaction with α lamellae. • Proposed 3D image processing methodology makes their segmentation possible. • Crack-lamellae orientation maps show prevalence of translamellar cracking. • Angle study comforts the influence of basal/prismatic slip on crack path.

36 MATERIALS SCIENCE↗
DOE OSTI2014

SU-E-QI-17: Dependence of 3D/4D PET Quantitative Image Features On Noise

Purpose: Quantitative imaging is a fast evolving discipline where a large number of features are extracted from images; i.e., radiomics. Some features have been shown to have diagnostic, prognostic and predictive value. However, they are sensitive to acquisition and processing factors; e.g., noise. In this study noise was added to positron emission tomography (PET) images to determine how features were affected by noise. Methods: Three levels of Gaussian noise were added to 8 lung cancer patients PET images acquired in 3D mode (static) and using respiratory tracking (4D); for the latter images from one of 10 phases were used. A total of 62 features: 14 shape, 19 intensity (1stO), 18 GLCM textures (2ndO; from grey level co-occurrence matrices) and 11 RLM textures (2ndO; from run-length matrices) features were extracted from segmented tumors. Dimensions of GLCM were 256×256, calculated using 3D images with a step size of 1 voxel in 13 directions. Grey levels were binned into 256 levels for RLM and features were calculated in all 13 directions. Results: Feature variation generally increased with noise. Shape features were the most stable while RLM were the most unstable. Intensity and GLCM features performed well; the latter being more robust. The most stable 1stO features were compactness, maximum and minimum length, standard deviation, root-mean-squared, I30, V10-V90, and entropy. The most stable 2ndO features were entropy, sum-average, sum-entropy, difference-average, difference-variance, difference-entropy, information-correlation-2, short-run-emphasis, long-run-emphasis, and run-percentage. In general, features computed from images from one of the phases of 4D scans were more stable than from 3D scans. Conclusion: This study shows the need to characterize image features carefully before they are used in research and medical applications. It also shows that the performance of features, and thereby feature selection, may be assessed in part by noise analysis.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1993

Direct 75 milliarcsecond images from the Multiple Mirror Telescope with adaptive optics

We report results from an adaptive optics system designed to provide imaging at the diffraction limit of resolution in the near-infrared at the Multiple Mirror Telescope (MMT). For the present experiment, the aperture consisted of five of the six primary mirrors of the MMT, operating as a coherently phased array. The largest components of the atmospherically induced wave-front aberration are the fluctuations in mean phase between the segments. These errors were derived in real time from the Fourier transform of short-exposure stellar images at 2.2 microns and corrected at an image of the telescope pupil with piston motion from a segmented adaptive mirror. At a correction rate of 43 Hz, this level of adaptive control resulted in an integrated image with a clear diffraction-limited component of 0.075 arcsec FWHM. This stabilized component is present directly in the light arriving at the detector and is not the result of postprocessing. We discuss future improvements to our adaptive wave-front control and its application to astronomical observations.

Lloyd-Hart, M.↗
DOE OSTI2016

WE-AB-BRA-09: Registration of Preoperative MRI to Intraoperative Radiographs for Automatic Vertebral Target Localization

Purpose: Accurate localization of target vertebrae is essential to safe, effective spine surgery, but wrong-level surgery occurs with surprisingly high frequency. Recent research yielded the “LevelCheck” method for 3D-2D registration of preoperative CT to intraoperative radiographs, providing decision support for level localization. We report a new method (MR-LevelCheck) to perform 3D-2D registration based on preoperative MRI, presenting a solution for the increasingly common scenario in which MRI (not CT) is used for preoperative planning. Methods: Direct extension of LevelCheck is confounded by large mismatch in image intensity between MRI and radiographs. The proposed method overcomes such challenges with a simple vertebrae segmentation. Using seed points at centroids, vertebrae are segmented using continuous max-flow method and dilated by 1.8 mm to include surrounding cortical bone (inconspicuous in T2w-MRI). MRI projections are computed (analogous to DRR) using segmentation and registered to intraoperative radiographs. The method was tested in a retrospective IRB-approved study involving 11 patients undergoing cervical, thoracic, or lumbar spine surgery following preoperative MRI. Registration accuracy was evaluated in terms of projection-distance-error (PDE) between the true and estimated location of vertebrae in each radiograph. Results: The method successfully registered each preoperative MRI to intraoperative radiographs and maintained desirable properties of robustness against image content mismatch, and large capture range. Segmentation achieved Dice coefficient = 89.2 ± 2.3 and mean-absolute-distance (MAD) = 1.5 ± 0.3 mm. Registration demonstrated robust performance under realistic patient variations, with PDE = 4.0 ± 1.9 mm (median ± iqr) and converged with run-time = 23.3 ± 1.7 s. Conclusion: The MR-LevelCheck algorithm provides an important extension to a previously validated decision support tool in spine surgery by extending its utility to preoperative MRI. With initial studies demonstrating PDE <5 mm and 0% failure rate, the method is now in translation to larger scale prospective clinical studies. S. Vogt and G. Kleinszig are employees of Siemens Healthcare.

60 APPLIED LIFE SCIENCES↗