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At least 1,333 records · Page 74

Information-Theoretic Exploration of Multivariate Time-Varying Image Databases

Modern scientific simulations produce very large datasets, making interactive exploration of such data computationally prohibitive. An increasingly common data reduction technique is to store visualizations and other data extracts in a database. The Cinema project is one such approach, storing visualizations in an image database for post hoc exploration and interactive image-based analysis. This work focuses on developing efficient algorithms that can quantify various types of multivariate dependencies existing within multi-variable datasets. It applies specific mutual information measures for the quantification of salient regions from multivariate image data. Here, using such information measures, the opacity of the images is modulated so that the salient regions are automatically highlighted and the domain scientists can interactively explore the most relevant regions for scientific discovery.

97 MATHEMATICS AND COMPUTING↗

A Comparative Study of the Perceptual Sensitivity of Topological Visualizations to Feature Variations

Color maps are a commonly used visualization technique in which data are mapped to optical properties, e.g., color or opacity. Color maps, however, do not explicitly convey structures (e.g., positions and scale of features) within data. Topology-based visualizations reveal and explicitly communicate structures underlying data. Although our understanding of what types of features are captured by topological visualizations is good, our understanding of people's perception of those features is not. Further, this paper evaluates the sensitivity of topology-based isocontour, Reeb graph, and persistence diagram visualizations compared to a reference color map visualization for synthetically generated scalar fields on 2-manifold triangular meshes embedded in 3D. In particular, we built and ran a human-subject study that evaluated the perception of data features characterized by Gaussian signals and measured how effectively each visualization technique portrays variations of data features arising from the position and amplitude variation of a mixture of Gaussians. For positional feature variations, the results showed that only the Reeb graph visualization had high sensitivity. For amplitude feature variations, persistence diagrams and color maps demonstrated the highest sensitivity, whereas isocontours showed only weak sensitivity. These results take an important step toward understanding which topology-based tools are best for various data and task scenarios and their effectiveness in conveying topological variations as compared to conventional color mapping.

97 MATHEMATICS AND COMPUTING↗

A real-time regional adaptive exposure method for saving dose-area product in x-ray fluoroscopy

Purpose: Reduction of radiation dose in x-ray imaging has been recognized as a high priority in the medical community. Here the authors show that a regional adaptive exposure method can reduce dose-area product (DAP) in x-ray fluoroscopy. The authors' method is particularly geared toward providing dose savings for the pediatric population. Methods: The scanning beam digital x-ray system uses a large-area x-ray source with 8000 focal spots in combination with a small photon-counting detector. An imaging frame is obtained by acquiring and reconstructing up to 8000 detector images, each viewing only a small portion of the patient. Regional adaptive exposure was implemented by varying the exposure of the detector images depending on the local opacity of the object. A family of phantoms ranging in size from infant to obese adult was imaged in anteroposterior view with and without adaptive exposure. The DAP delivered to each phantom was measured in each case, and noise performance was compared by generating noise arrays to represent regional noise in the images. These noise arrays were generated by dividing the image into regions of about 6 mm{sup 2}, calculating the relative noise in each region, and placing the relative noise value of each region in a one-dimensional array (noise array) sorted from highest to lowest. Dose-area product savings were calculated as the difference between the ratio of DAP with adaptive exposure to DAP without adaptive exposure. The authors modified this value by a correction factor that matches the noise arrays where relative noise is the highest to report a final dose-area product savings. Results: The average dose-area product saving across the phantom family was (42 {+-} 8)% with the highest dose-area product saving in the child-sized phantom (50%) and the lowest in the phantom mimicking an obese adult (23%). Conclusions: Phantom measurements indicate that a regional adaptive exposure method can produce large DAP savings without compromising the noise performance in the image regions with highest noise.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Large scale validation of the M5L lung CAD on heterogeneous CT datasets

Purpose: M5L, a fully automated computer-aided detection (CAD) system for the detection and segmentation of lung nodules in thoracic computed tomography (CT), is presented and validated on several image datasets. Methods: M5L is the combination of two independent subsystems, based on the Channeler Ant Model as a segmentation tool [lung channeler ant model (lungCAM)] and on the voxel-based neural approach. The lungCAM was upgraded with a scan equalization module and a new procedure to recover the nodules connected to other lung structures; its classification module, which makes use of a feed-forward neural network, is based of a small number of features (13), so as to minimize the risk of lacking generalization, which could be possible given the large difference between the size of the training and testing datasets, which contain 94 and 1019 CTs, respectively. The lungCAM (standalone) and M5L (combined) performance was extensively tested on 1043 CT scans from three independent datasets, including a detailed analysis of the full Lung Image Database Consortium/Image Database Resource Initiative database, which is not yet found in literature. Results: The lungCAM and M5L performance is consistent across the databases, with a sensitivity of about 70% and 80%, respectively, at eight false positive findings per scan, despite the variable annotation criteria and acquisition and reconstruction conditions. A reduced sensitivity is found for subtle nodules and ground glass opacities (GGO) structures. A comparison with other CAD systems is also presented. Conclusions: The M5L performance on a large and heterogeneous dataset is stable and satisfactory, although the development of a dedicated module for GGOs detection could further improve it, as well as an iterative optimization of the training procedure. The main aim of the present study was accomplished: M5L results do not deteriorate when increasing the dataset size, making it a candidate for supporting radiologists on large scale screenings and clinical programs.

60 APPLIED LIFE SCIENCES↗

Predicting adenocarcinoma recurrence using computational texture models of nodule components in lung CT

Purpose: To investigate the importance of presurgical computed tomography (CT) intensity and texture information from ground-glass opacities (GGO) and solid nodule components for the prediction of adenocarcinoma recurrence. Methods: For this study, 101 patients with surgically resected stage I adenocarcinoma were selected. During the follow-up period, 17 patients had disease recurrence with six associated cancer-related deaths. GGO and solid tumor components were delineated on presurgical CT scans by a radiologist. Computational texture models of GGO and solid regions were built using linear combinations of steerable Riesz wavelets learned with linear support vector machines (SVMs). Unlike other traditional texture attributes, the proposed texture models are designed to encode local image scales and directions that are specific to GGO and solid tissue. The responses of the locally steered models were used as texture attributes and compared to the responses of unaligned Riesz wavelets. The texture attributes were combined with CT intensities to predict tumor recurrence and patient hazard according to disease-free survival (DFS) time. Two families of predictive models were compared: LASSO and SVMs, and their survival counterparts: Cox-LASSO and survival SVMs. Results: The best-performing predictive model of patient hazard was associated with a concordance index (C-index) of 0.81 ± 0.02 and was based on the combination of the steered models and CT intensities with survival SVMs. The same feature group and the LASSO model yielded the highest area under the receiver operating characteristic curve (AUC) of 0.8 ± 0.01 for predicting tumor recurrence, although no statistically significant difference was found when compared to using intensity features solely. For all models, the performance was found to be significantly higher when image attributes were based on the solid components solely versus using the entire tumors (p < 3.08 × 10{sup −5}). Conclusions: This study constitutes a novel perspective on how to interpret imaging information from CT examinations by suggesting that most of the information related to adenocarcinoma aggressiveness is related to the intensity and morphological properties of solid components of the tumor. The prediction of adenocarcinoma relapse was found to have low specificity but very high sensitivity. Our results could be useful in clinical practice to identify patients for which no recurrence is expected with a very high confidence using a presurgical CT scan only. It also provided an accurate estimation of the risk of recurrence after a given duration t from surgical resection (i.e., C-index = 0.81 ± 0.02)

60 APPLIED LIFE SCIENCES↗

WE-FG-202-03: Quantitative CT-Based Analysis to Assess Lung Injury Following Proton Radiotherapy

Purpose: Relative to photon alternatives, the increased dose-conformity associated with proton therapy is expected to reduce the extent of radiation-induced lung toxicity. However, analysis of follow-up data is yet to be published in this area. In this study we retrospectively analyzed late-phase HU changes for proton therapy cohorts of chest wall and lung patients. Methods: From our institution’s register of patients treated using double-scattered protons, all chest wall and stereotactic lung cases (treated 2011–2012 and 2008–2014 respectively) were initially considered. Follow-up CT data were accessible for 10 chest wall cases (prescribed 50.4 GyRBE in 28 fractions) and 16 lung cases (prescribed 42–50 GyRBE in 3–4 fractions). CT time-points ranged from 0.5–3.5 years post-treatment. Planning doses were recalculated using TOPAS Monte Carlo simulations and mapped onto the follow-up images using deformable registration. Excluding internal target volumes, changes in HU between each patient’s planning and follow-up CT(s) were evaluated for dose bins of 2–30 GyRBE (2 GyRBE increments). Results: Linear increases in HU per unit dose, with correlations statistically significant at the 1% level (one-sided Spearman’s rank test), were evident for all 10 chest wall cases and 14/16 lung cases. The mean changes in HU/Gy were: 1.76 (SD=0.73) for the chest wall cohort, and 1.40 (SD=0.87) for the lung cohort. The median scan times post treatment were 21 and 12 months respectively. All 26 patients developed solid consolidation (scar-like radiographic opacities) within the exposed lung(s). Conclusion: Analysis of follow-up CTs revealed statistically significant correlations in HU-change/dose for two proton cohorts (lung and chest wall). Quantitatively, the late-phase changes we report broadly match published photon data. Further analysis of such radiographic changes, particularly via matched cohort studies drawing upon consistent imaging protocols, could play an important role in elucidating inter-modality differences and provide insight into proton RBE for lung injury. Tracy Underwood gratefully acknowledges the support of the European Commission under an FP7 Marie Curie International Outgoing Fellowship for Career Development (#630064). This work was also funded under U19 grant CA 021239 (PI: Delaney).

60 APPLIED LIFE SCIENCES↗

TH-AB-207A-09: Tailoring TCM Schemes to a Task: Evaluating the Impact of Customized TCM Profiles On Detection of Lung Nodules in Simulated CT Lung Cancer Screening

Purpose: Recent work has shown that current TCM profile designs boost detection of low-contrast lung lesions in the lung apices, but yield reduced detection performance in the mid and lower lung regions relative to fixed tube current cases. This observed imbalance suggests that the TCM scheme might be tailored in new ways to maximize nodule detection throughout the entire lung. In this work, we begin a preliminary investigation into custom TCM profiles in an attempt to achieve uniform lesion detection throughout the extent of the lung. Methods: Low-contrast (25HU), 6mm nodules representing ground glass opacities were simulated at 1mm intervals over the length the lungs in a voxelized model of the XCAT phantom, one nodule per lung, per simulated scan. Voxel values represented attenuation values at 80keV. CT projection data was created by simulating a finite focal spot and using Joseph’s method for forward projection; scanner geometry was that of the Siemens Sensation 64 and the X-ray source was simulated as an 80keV monochromatic beam. Noise realizations were created using Poisson statistics, a realistic bowtie filter and varying tube current. 500 noise realizations were created for the custom TCM designs. All reconstruction was done with FreeCT-wFBP. An SKE/BKE task was used in conjunction with a 2D Hotelling Observer to calculate area-under-the-curve (AUC) as a proxy for “detectability.” AUC was plotted as a function of nodule Z-location to create a “detectability map.” The detectability map for the custom TCM curve was qualitatively assessed relative to previous results for the fixed TC and clinical TCM cases for uniformity. Results: Detection uniformity was improved throughout the mid and lower lungs, however detection remained disproportionately high in the upper lung region. Conclusion: Detection uniformity was improved with a custom TC profile. Future work will incorporate an analytic, task-specific approach to optimize the TC scheme for nodule detection. J. Hoffman: Part-time intern, Toshiba Medical Research Institute; M. McNitt-Gray: Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics; F. Noo: Institutional research agreement, Siemens Healthcare; Receives research funding from Siemens Healthcare.

60 APPLIED LIFE SCIENCES↗

A gamma-ray determination of the Universe’s star formation history

Here, the light emitted by all galaxies over the history of the Universe produces the extragalactic background light (EBL) at ultraviolet, optical, and infrared wavelengths. The EBL is a source of opacity for gamma rays via photon-photon interactions, leaving an imprint in the spectra of distant gamma-ray sources. We measured this attenuation using 739 active galaxies and one gamma-ray burst detected by the Fermi Large Area Telescope. This allowed us to reconstruct the evolution of the EBL and determine the star formation history of the Universe over 90% of cosmic time. Our star formation history is consistent with independent measurements from galaxy surveys, peaking at redshift z ~ 2. Upper limits of the EBL at the epoch of reionization suggest a turnover in the abundance of faint galaxies at z ~ 6.

79 ASTRONOMY AND ASTROPHYSICS↗

Bulk and Spatially Resolved Extracellular Metabolome of Free-Living Nitrogen Fixation

Free-living nitrogen-fixing bacteria contribute significantly to terrestrial nitrogen availability; however, the forms of nitrogen contributed by this process are poorly understood. This is in part because of inherent challenges to studying soil microorganisms in situ , such as vast differences in scale between microorganism and ecosystem and complexities of the soil system (e.g., opacity, chemical complexity).

59 BASIC BIOLOGICAL SCIENCES↗

Reduced Hardware NOrec: A Safe and Scalable Hybrid Transactional Memory

Because of hardware TM limitations, software fallbacks are the only way to make TM algorithms guarantee progress. Nevertheless, all known software fallbacks to date, from simple locks to sophisticated versions of the NOrec Hybrid TM algorithm, have either limited scalability or weakened semantics. We propose a novel reduced-hardware (RH) version of the NOrec HyTM algorithm. Instead of an all-software slow path, in our RH NOrec the slow-path is a "mix" of hardware and software: one short hardware transaction executes a maximal amount of initial reads in the hardware, and the second executes all of the writes. Furthermore, this novel combination of the RH approach and the NOrec algorithm delivers the first Hybrid TM that scales while fully preserving the hardware's original semantics of opacity and privatization. Our GCC implementation of RH NOrec is promising in that it shows improved performance relative to all prior methods, at the concurrency levels we could test today.

97 MATHEMATICS AND COMPUTING↗

Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification

The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms.

59 BASIC BIOLOGICAL SCIENCES↗

ROVER

ROVER Is an application for distributed-memory volume rendering and simulated radiography focused on many-core architectures (e.g., GPU, CPU, and MIC). Volume rendering, also known as volume visualization, is a commonly used scientific visualization algorithm that enables users to visualize an entire scalar field at once by mapping scalar values to colors and transparency. Simulated radiography Is a generalization of the volume rendering algorithm from four color channels (I.e., red, green, blue, and transparency) to an arbitrary number of channels representing material opacities in discrete energy groups, measured In electron volts.

Larsen, Matthew↗

SuperNu Version 4.x

We seek to release SuperNu, Version 4.x, as a continuation of development for the open source SuperNu software. The SuperNu, Version 3.x Monte Carlo radiative transfer code for astrophysical transients was released with GPLv3 copyright, asserted by LANL in 2015. For the next release we have features planned for development , including: opacity implementation (including non-local thermodynamic equilibrium effects), generalized source implementation (e.g. for emulating shock heating in Type II supernovae), 3T (electron, ion, radiation) internal energy update, special relativity corrections through O(v^2/c^2), light polarization (e.g. for comparison to spectroplarimetry observations of supernovae and kilonovae), and infrastructure features (checkpoint and restart of simulations, and tools including setup and Slurm batch scripts and simulation post-processing/analysis scripts). These features are intended to improve the fidelity and/or better understand uncertainty in supernova and kilonova light curve calculations.

Wollaeger, Ryan↗

Multiscale X-ray phase contrast imaging of human cartilage for investigating osteoarthritis formation

The evolution of cartilage degeneration is still not fully understood, partly due to its thinness, low radio-opacity and therefore lack of adequately resolving imaging techniques. X-ray phase-contrast imaging (X-PCI) offers increased sensitivity with respect to standard radiography and CT allowing an enhanced visibility of adjoining, low density structures with an almost histological image resolution. This study examined the feasibility of X-PCI for high-resolution (sub-) micrometer analysis of different stages in tissue degeneration of human cartilage samples and compare it to histology and transmission electron microscopy. Ten 10%-formalin preserved healthy and moderately degenerated osteochondral samples, post-mortem extracted from human knee joints, were examined using four different X-PCI tomographic set-ups using synchrotron radiation the European Synchrotron Radiation Facility (France) and the Swiss Light Source (Switzerland). Volumetric datasets were acquired with voxel sizes between 0.7 × 0.7 × 0.7 and 0.1 × 0.1 × 0.1 µm 3 . Data were reconstructed by a filtered back-projection algorithm, post-processed by ImageJ, the WEKA machine learning pixel classification tool and VGStudio max. For correlation, osteochondral samples were processed for histology and transmission electron microscopy. X-PCI provides a three-dimensional visualization of healthy and moderately degenerated cartilage samples down to a (sub-)cellular level with good correlation to histologic and transmission electron microscopy images. X-PCI is able to resolve the three layers and the architectural organization of cartilage including changes in chondrocyte cell morphology, chondrocyte subgroup distribution and (re-)organization as well as its subtle matrix structures. X-PCI captures comprehensive cartilage tissue transformation in its environment and might serve as a tissue-preserving, staining-free and volumetric virtual histology tool for examining and chronicling cartilage behavior in basic research/laboratory experiments of cartilage disease evolution.

3D analysis↗

Quantitative Defect Analysis of Ablator Capsule Surfaces Using a Leica Confocal Microscope and a High-Density Atomic Force Microscope

High-density carbon (HDC) is being evaluated as an alternative to the current National Ignition Facility (NIF) point-design ablator material (glow discharge plasma, or GDP, plastic) due to its high density and optimal opacity, which leads to a higher implosion velocity. Chemical-vapor-deposition-coated HDC capsules have a near perfect surface figure but a microscopically rough surface. After polishing, the surface becomes smooth at nanometer scales but has numerous micron-sized surface pits, whose volumes, morphology, and distribution must be quantified to guide NIF target selection. Traditional metrology tools for GDP surface defects, such as the atomic force microscope (AFM) based Spheremapper and a phase-shifting differential interferometer, lack the resolution to characterize these localized features. In this paper, we describe how this metrology challenge is met by developing automated surface metrology solutions based on a high-density (HD) AFM and a Leica confocal microscope. Furthermore, these tools are complementary in nature. HD-AFM has a 0.1-μm spatial resolution and determines the overall shape distortion and pit statistics by tracing great circles on a capsule with high throughput.

36 MATERIALS SCIENCE↗

Particle velocity measurement within a free-falling particle curtain using microscopic shadow velocimetry

We report an optical method for particle velocity measurement that is suitable for the measurement of particle velocities within dense particle-laden flows with high spatial resolution. The technique is based on particle shadow velocimetry with the use of a long-distance microscopic lens for images collection. The narrow depth of field of the lens allows particles within the focal plane to have much higher pattern intensities than those outside it on the collected images. Data processing was then employed to remove particles from outside the focal plane based on the gradient of the signal and a threshold. Following this, particle velocity was calculated from two successive images in the usual way. The technique was successfully demonstrated in a free-falling particle curtain with volume fractions in the four-way coupling regime of near-spherical micro-particles falling under gravity. The method was successfully employed to measure the transverse velocity profile through the curtain, which is the first time that such a measurement has been performed. Other highly-fidelity experimental data, which is also well suited to model development and validation, include the particle mass flow rate, curtain thickness and opacity.

Han, Shipu (ORCID:0000000278545882)↗

Flow Measurements in a Blood-Perfused Collagen Vessel Using X-Ray Micro-Particle Image Velocimetry

Blood-perfused tissue models are joining the emerging field of tumor engineering because they provide new avenues for modulation of the tumor microenvironment and preclinical evaluation of the therapeutic potential of new treatments. The characterization of fluid flow parameters in such in-vitro perfused tissue models is a critical step towards better understanding and manipulating the tumor microenvironment. However, traditional optical flow measurement methods are inapplicable because of the opacity of blood and the thickness of the tissue sample. In order to overcome the limitations of optical method we demonstrate the feasibility of using phase-contrast x-ray imaging to perform microscale particle image velocimetry (PIV) measurements of flow in blood perfused hydrated tissue-representative microvessels. However, phase contrast x-ray images significantly depart from the traditional PIV image paradigm, as they have high intensity background, very low signal-to-noise ratio, and volume integration effects. Hence, in order to achieve accurate measurements special attention must be paid to the image processing and PIV cross-correlation methodologies. Therefore we develop and demonstrate a methodology that incorporates image preprocessing as well as advanced PIV crosscorrelation methods to result in measured velocities within experimental uncertainty.

59 BASIC BIOLOGICAL SCIENCES↗

Monitoring the impact of confinement on hyphal penetration and fungal behavior

Through their expansive mycelium network, soil fungi alter the physical arrangement and chemical composition of their local environment. This can significantly impact bacterial distribution and nutrient transport and can play a dramatic role in shaping the rhizosphere around a developing plant. However, direct observation and quantitation of such behaviors is extremely difficult due to the opacity and complex porosity of the soil microenvironment. In this study, we demonstrate the development and use of an engineered microhabitat to visualize fungal growth in response to varied levels of confinement. Microfluidics were fabricated using photolithography and conventional soft lithography, assembled onto glass slides, and prepared to accommodate fungal cultures. Selected fungal strains across three phyla (Ascomycota: Morchella sextalata , Fusarium falciforme ; Mucoromycota: Linnemannia elongata , Podila minutissima , Benniella ; Basidiomycota: Laccaria bicolor , and Serendipita sp.) were cultured within microhabitats and imaged using time-lapse microscopy to visualize development at the mycelial level. Fungal hyphae of each strain were imaged as they penetrated through microchannels with well-defined pore dimensions. The hyphal penetration rates through the microchannels were quantified via image analysis. Other behaviors, including differences in the degree of branching, peer movement, and tip strength were also recorded for each strain. Our results provide a repeatable and easy-to-use approach for culturing fungi within a microfluidics platform and for visualizing the impact of confinement on hyphal growth and other fungal behaviors pertinent to their remodeling of the underground environment.

Guo, Yi-Syuan (ORCID:0000000340142225)↗