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At least 469 records · Page 26

Distributed computing strategies for processing of FT-ICR MS imaging datasets for continuous mode data visualization

High-resolution Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging enables the spatial mapping and identification of biomolecules from complex surfaces. The need for long time-domain transients, and thus large raw file sizes, results in a large amount of raw data (“big data”) that must be processed efficiently and rapidly. This can be compounded by largearea imaging and/or high spatial resolution imaging. For FT-ICR, data processing and data reduction must not compromise the high mass resolution afforded by the mass spectrometer. The continuous mode “Mosaic Datacube” approach allows high mass resolution visualization (0.001 Da) of mass spectrometry imaging data, but requires additional processing as compared to featurebased processing. We describe the use of distributed computing for processing of FT-ICR MS imaging datasets with generation of continuous mode Mosaic Datacubes for high mass resolution visualization. An eight-fold improvement in processing time is demonstrated using a Dutch nationally available cloud service.

Environmental Molecular Sciences Laboratory↗

How “hot” are hotspots: Statistically localizing the high-activity areas on soil and rhizosphere images

The topic of microbial hotspots in soil requires not only visualizing their spatial distribution and biochemical analyses, but also statistical approaches to identify these hotspots and separate them from the surrounding activities (background). We hypothesized that each hotspot type (e.g. enzyme activities in the rhizosphere, root exudation, localization of herbicide accumulation) is a result of local process driven by biotic and/or abiotic factors, and the process rates in the hotspots are much faster than those in the soil background. We further hypothesized that the background and hotspot activities in soil belong to different statistical distributions. Consequently, hotspot determination should be based on statistical separation of activities significantly higher than the background. We analyzed for the statistical distributions of grey values on three groups of published images: 1) 14 C images of carbon input by roots into the rhizosphere, 2) 14 C glyphosate accumulation in the plant, and 3) zymogram of leucine aminopeptidase activity in rooted soil. The two Gaussian distributions were fit (the first representing the background, the second the hotspots) to the distribution of grey values in the images, the parameters (means and standard deviations, SD) of the fitted distributions were calculated, and the background was removed. Thus, we identified hotspots as areas outside of the Mean+2SD image intensity (corresponding to the upper ~ 2.5% of activity, being over 97.5% of background values) and finally, visualized images of solely hotspot locations. Finally, these results were compared with previously used decisions on hotspot intensity thresholding (i.e. Top-25% and 17 standard thresholding approaches in ImageJ) and discussed the advantages of the Mean+2SD as well as Mean+3SD approaches. These advantages include: i) simple unification of the thresholding approach for several imaging methods with various principles of activity distribution, ii) identification of hotspots with various activity levels, iii) analysis of “time-specific” hotspots in temporal sequences of images. Compared with 17 standard thresholding methods, we concluded that objectively elucidating and separating the hotspots should be based on statistical distribution analysis, e.g. using the Mean+2SD or Mean+3SD approaches. Furthermore, this simple Mean+2SD approach delivered suitable results for three groups of images and so, helps to understand the processes responsible for the highest activities and elucidate hotspots.

59 BASIC BIOLOGICAL SCIENCES↗

An effective survey method for studying volant species activity and behavior at tall structures

The effects of anthropogenic modification of air space on wildlife, particularly volant species, is not fully understood. Thus, it is essential to understand wildlife-interactions with tall structures to implement effective mitigation strategies. Yet, we are currently lacking standard protocols for visual surveys of wildlife behavior at such heights. Our study sought to determine an effective, repeatable method using readily available night vision and thermal technology to survey wildlife at tall structures. Using bats as the taxonomic group of interest, we (1) created a key to identify bats and their behavior, (2) compared the effectiveness of 2 different technologies, and (3) assessed optimal equipment placement to visually capture bat activity and behavior in proximity to wind turbine towers. For the latter, we tested thermal cameras at four distances from the base of the tower. The results of our study revealed that thermal cameras captured ∼34% more flying animals than night vision at a 2 m distance. However, due to the heat signature of the turbine towers themselves, it was challenging to identify behaviors and interactions that occurred in close proximity to the towers. In contrast, it was difficult to identify bats approaching the towers using night vision, yet we were able to clearly observe interactions with the towers themselves. With regards to equipment placement, we visually captured more bats with the thermal cameras placed 2 m from the tower base compared to farther distances. From our findings, we recommend that when using either thermal or night vision technology at tall structures, they be placed 2 m from the base to effectively observe interactions along the length of these structures. In addition, we further recommend that consideration be given to the use of these two technology types together to effectively conduct such surveys. If these survey techniques are incorporated into standard protocols, future surveys at a variety of tall structures are likely to become comparable and repeatable, thereby more effectively informing any mitigation strategies that may be required.

54 ENVIRONMENTAL SCIENCES↗

Covisualization by computational optical-sectioning microscopy of integrin and associated proteins at the cell membrane of living onion protoplasts

Using higher-resolution wide-field computational optical-sectioning fluorescence microscopy, the distribution of antigens recognized by antibodies against animal beta 1 integrin, fibronectin, and vitronectin has been visualized at the outer surface of enzymatically protoplasted onion epidermis cells and in depectinated cell wall fragments. On the protoplast all three antigens are colocalized in an array of small spots, as seen in raw images, in Gaussian filtered images, and in images restored by two different algorithms. Fibronectin and vitronectin but not beta 1 integrin antigenicities colocalize as puncta in comparably prepared and processed images of the wall fragments. Several control visualizations suggest considerable specifity of antibody recognition. Affinity purification of onion cell extract with the same anti-integrin used for visualization has yielded protein that separates in SDS-PAGE into two bands of about 105-110 and 115-125 kDa. These bands are again recognized by the visualization antibody, which was raised against the extracellular domain of chicken beta 1 integrin, and are also recognized by an antibody against the intracellular domain of chicken beta 1 integrin. Because beta 1 integrin is a key protein in numerous animal adhesion sites, it appears that the punctate distribution of this protein in the cell membranes of onion epidermis represents the adhesion sites long known to occur in cells of this tissue. Because vitronectin and fibronection are matrix proteins that bind to integrin in animals, the punctate occurrence of antigenically similar proteins both in the wall (matrix) and on enzymatically prepared protoplasts reinforces the concept that onion cells have adhesion sites with some similarity to certain kinds of adhesion sites in animals.

NASA Discipline Plant Biology↗

SLoWPoKES-II: 100,000 WIDE BINARIES IDENTIFIED IN SDSS WITHOUT PROPER MOTIONS

We present the Sloan Low-mass Wide Pairs of Kinematically Equivalent Stars (SLoWPoKES)-II catalog of low-mass visual binaries identified from the Sloan Digital Sky Survey (SDSS) by matching photometric distances. The candidate pairs are vetted by comparing the stellar information. The candidate pairs are vetted by comparing the stellar density at their respective Galactic positions to Monte Carlo realizations of a simulated Milky Way. In this way, we are able to identify large numbers of bona fide wide binaries without the need for proper motions. Here, 105,537 visual binaries with angular separations of ∼1–20″ were identified, each with a probability of chance alignment of ≤5%. This is the largest catalog of bona fide wide binaries to date, and it contains a diversity of systems—in mass, mass ratios, binary separations, metallicity, and evolutionary states—that should facilitate follow-up studies to characterize the properties of M dwarfs and white dwarfs. There is a subtle but definitive suggestion of multiple populations in the physical separation distribution, supporting earlier findings. We suggest that wide binaries are composed of multiple populations, most likely representing different formation modes. There are 141 M7 or later wide binary candidates, representing a seven-fold increase over the number currently known. These binaries are too wide to have been formed via the ejection mechanism. Finally, we found that 6% of spectroscopically confirmed M dwarfs are not included in the SDSS STAR catalog; they are misclassified as extended sources due to the presence of a nearby or partially resolved companion. The SLoWPoKES-II catalog is publicly available to the entire community on the World Wide Web via the Filtergraph data visualization portal.

79 ASTRONOMY AND ASTROPHYSICS↗

Integrated Computational System for Aerodynamic Steering and Visualization

In February of 1994, an effort from the Fluid Dynamics and Information Sciences Divisions at NASA Ames Research Center with McDonnel Douglas Aerospace Company and Stanford University was initiated to develop, demonstrate, validate and disseminate automated software for numerical aerodynamic simulation. The goal of the initiative was to develop a tri-discipline approach encompassing CFD, Intelligent Systems, and Automated Flow Feature Recognition to improve the utility of CFD in the design cycle. This approach would then be represented through an intelligent computational system which could accept an engineer's definition of a problem and construct an optimal and reliable CFD solution. Stanford University's role focused on developing technologies that advance visualization capabilities for analysis of CFD data, extract specific flow features useful for the design process, and compare CFD data with experimental data. During the years 1995-1997, Stanford University focused on developing techniques in the area of tensor visualization and flow feature extraction. Software libraries were created enabling feature extraction and exploration of tensor fields. As a proof of concept, a prototype system called the Integrated Computational System (ICS) was developed to demonstrate CFD design cycle. The current research effort focuses on finding a quantitative comparison of general vector fields based on topological features. Since the method relies on topological information, grid matching and vector alignment is not needed in the comparison. This is often a problem with many data comparison techniques. In addition, since only topology based information is stored and compared for each field, there is a significant compression of information that enables large databases to be quickly searched. This report will (1) briefly review the technologies developed during 1995-1997 (2) describe current technologies in the area of comparison techniques, (4) describe the theory of our new method researched during the grant year (5) summarize a few of the results and finally (6) discuss work within the last 6 months that are direct extensions from the grant.

Hesselink, Lambertus↗

Spatial profiling of the interplay between cell type- and vision-dependent transcriptomic programs in the visual cortex

How early sensory experience during “critical periods” of postnatal life affects the organization of the mammalian neocortex at the resolution of neuronal cell types is poorly understood. We previously reported that the functional and molecular profiles of layer 2/3 (L2/3) cell types in the primary visual cortex (V1) are vision-dependent [S. Chenget al.,Cell185, 311–327.e24 (2022)]. Here, we characterize the spatial organization of L2/3 cell types with and without visual experience. Spatial transcriptomic profiling based on 500 genes recapitulates the zonation of L2/3 cell types along the pial–ventricular axis in V1. By applying multitasking theory, we suggest that the spatial zonation of L2/3 cell types is linked to the continuous nature of their gene expression profiles, which can be represented as a 2D manifold bounded by three archetypal cell types. By comparing normally reared and dark reared L2/3 cells, we show that visual deprivation-induced transcriptomic changes comprise two independent gene programs. The first, induced specifically in the visual cortex, includes immediate-early genes and genes associated with metabolic processes. It manifests as a change in cell state that is orthogonal to cell-type-specific gene expression programs. By contrast, the second program impacts L2/3 cell-type identity, regulating a subset of cell-type-specific genes and shifting the distribution of cells within the L2/3 cell-type manifold. Through an integrated analysis of spatial transcriptomics with single-nucleus RNA-seq data, we describe how vision patterns cortical L2/3 cell types during the critical period.

Science & Technology - Other Topics↗

Diffuse interstellar bands versus known atomic and molecular species in the interstellar medium of M82 toward SN 2014J

We discuss the absorption due to various constituents of the interstellar medium (ISM) of M82 seen in moderately high-resolution, high signal-to-noise ratio optical spectra of SN 2014J. Complex absorption from M82 is seen, at velocities 45 ≲ v {sub LSR} ≲ 260 km s{sup –1}, for Na I, K I, Ca I, Ca II, CH, CH{sup +}, and CN; many of the diffuse interstellar bands (DIBs) are also detected. Comparisons of the column densities of the atomic and molecular species and the equivalent widths of the DIBs reveal both similarities and differences in relative abundances, compared to trends seen in the ISM of our Galaxy and the Magellanic Clouds. Of the 10 relatively strong DIBs considered here, 6 (including λ5780.5) have strengths within ±20% of the mean values seen in the local Galactic ISM, for comparable N(K I); 2 are weaker by 20%-45% and 2 (including λ5797.1) are stronger by 25%-40%. Weaker than 'expected' DIBs (relative to N(K I), N(Na I), and E(B – V)) in some Galactic sight lines and toward several other extragalactic supernovae appear to be associated with strong CN absorption and/or significant molecular fractions. While the N(CH)/N(K I) and N(CN)/N(CH) ratios seen toward SN 2014J are similar to those found in the local Galactic ISM, the combination of high N(CH{sup +})/N(CH) and high W(5797.1)/W(5780.5) ratios has not been seen elsewhere. The centroids of many of the M82 DIBs are shifted relative to the envelope of the K I profile—likely due to component-to-component variations in W(DIB)/N(K I) that may reflect the molecular content of the individual components. We compare estimates for the host galaxy reddening E(B – V) and visual extinction A {sub V} derived from the various interstellar species with the values estimated from optical and near-IR photometry of SN 2014J.

79 ASTRONOMY AND ASTROPHYSICS↗

Computational flow simulation of liquid oxygen in a SSME preburner injector element LOX post

Liquid oxygen (LOX) is simulated as an incompressible flow through a Space Shuttle main engine fuel preburner injector element LOX post for the full range of operating conditions. Axial profiles of axial velocity and static pressure are presented. For each operating condition analyzed, the minimum pressure downstream of the orifice is compared to the vapor pressure to determine if cavitation could occur. Flow visualization is provided by velocity vectors and stream function contours. The results indicate that the minimum pressure is too high for cavitation to occur. To establish confidence in the CFD analysis, the simulation is repeated with water flow through a superscaled LOX post and compared with experimental results. The agreement between calculated and experimental results is very good.

Rocker, Marvin↗

Lunar Terrain Mapping Using 3D Software and Modeling Techniques for the Glenn Research Center Communication Analysis Suite

As NASA prepares to return humans to the Moon as part of upcoming Artemis missions, engineers must examine the surface features and safety of lunar terrain at various locations. The Glenn Research Center Communication Analysis Suite (GCAS) includes visualization tools developed to aid scientists in this quest to comprehend lunar terrain data, as well as spatial communication information. Visual information and understanding will be highly useful to engineers as they use the GCAS to compare the topography of regions of interest for the Artemis III and future space travel missions. Not only can three-dimensional (3D) visualization display the intricacies of the lunar terrain, but it can also demonstrate relationships such as the presence or absence of communication links between Earth ground stations, lunar crew members, and rovers, and the presence of shadows on the lunar surface. In the future, the GCAS has the potential to support the planning of other space exploration missions as well. The emerging possibility of incorporating more planetary bodies becomes especially important as NASA plans not only to return to the Moon but to press onward to Mars.

Visualization↗

Wind Tunnel Testing of AFC over a Deflected Aileron on the High-Lift Common Research Model

Active flow control (AFC) using discrete fluidic actuators distributed along the span, just upstream of the deflected aileron of the 10% scale high-lift version of the Common Research Model (CRM-HL), was evaluated during a wind tunnel test in the NASA Langley 14- by 22-Foot Subsonic Tunnel. For this set of experiments, a new outboard section was fabricated incorporating a deflectable aileron. Aileron deflection angles of 0, 7.5, 16, and 25 were investigated. This experimental investigation is in response to a recent study by Boeing potential to use AFC with a drooped aileron during takeoff to improve lift-to-drag ratio (L/D) by as much as 5%, depending on AFC mass flow rate. AFC is used at deflection angles above the nominal deflection of 7.5 to control the resulting flow separation that occurs and potentially improve L/D. Improvements in aircraft low-speed L/D can affect vehicle range and/or payload. Tuft flow visualization data, steady and unsteady surface pressure data, and force and moment data are used to compare the flowfields with and without AFC. Parameters varied include actuator momentum coefficient and aileron deflection angle. The surface pressure and tuft flow visualization results indicate that without AFC, the flow over a majority of the aileron upper surface is separated for aileron deflection angles larger than 7.5. When AFC is applied, the flow is reattached to the aileron. Force and moment results show that a local increase in lift leads to an increase in L/D of at least 3.5% using mass flow rates thought to be available from air sources onboard a commercial transport.

AFC↗

Wind Tunnel Testing of AFC over a Deflected Aileron on the High-Lift Common Research Model

Active flow control (AFC) using discrete fluidic actuators distributed along the span, just upstream of the deflected aileron of the 10% scale high-lift version of the Common Research Model (CRM-HL), was evaluated during a wind tunnel test in the NASA Langley 14- by 22-Foot Subsonic Tunnel. For this set of experiments, a new outboard section was fabricated incorporating a deflectable aileron. Aileron deflection angles of 0, 7.5, 16, and 25 were investigated. This experimental investigation is in response to a recent study by Boeing potential to use AFC with a drooped aileron during takeoff to improve lift-to-drag ratio (L/D) by as much as 5%, depending on AFC mass flow rate. AFC is used at deflection angles above the nominal deflection of 7.5 to control the resulting flow separation that occurs and potentially improve L/D. Improvements in aircraft low-speed L/D can affect vehicle range and/or payload. Tuft flow visualization data, steady and unsteady surface pressure data, and force and moment data are used to compare the flowfields with and without AFC. Parameters varied include actuator momentum coefficient and aileron deflection angle. The surface pressure and tuft flow visualization results indicate that without AFC, the flow over a majority of the aileron upper surface is separated for aileron deflection angles larger than 7.5. When AFC is applied, the flow is reattached to the aileron. Force and moment results show that a local increase in lift leads to an increase in L/D of at least 3.5% using mass flow rates thought to be available from air sources onboard a commercial transport.

AFC↗

Multitaper Spectral Analysis and Wavelet Denoising Applied to Helioseismic Data

Estimates of solar normal mode frequencies from helioseismic observations can be improved by using Multitaper Spectral Analysis (MTSA) to estimate spectra from the time series, then using wavelet denoising of the log spectra. MTSA leads to a power spectrum estimate with reduced variance and better leakage properties than the conventional periodogram. Under the assumption of stationarity and mild regularity conditions, the log multitaper spectrum has a statistical distribution that is approximately Gaussian, so wavelet denoising is asymptotically an optimal method to reduce the noise in the estimated spectra. We find that a single m-upsilon spectrum benefits greatly from MTSA followed by wavelet denoising, and that wavelet denoising by itself can be used to improve m-averaged spectra. We compare estimates using two different 5-taper estimates (Stepian and sine tapers) and the periodogram estimate, for GONG time series at selected angular degrees l. We compare those three spectra with and without wavelet-denoising, both visually, and in terms of the mode parameters estimated from the pre-processed spectra using the GONG peak-fitting algorithm. The two multitaper estimates give equivalent results. The number of modes fitted well by the GONG algorithm is 20% to 60% larger (depending on l and the temporal frequency) when applied to the multitaper estimates than when applied to the periodogram. The estimated mode parameters (frequency, amplitude and width) are comparable for the three power spectrum estimates, except for modes with very small mode widths (a few frequency bins), where the multitaper spectra broadened the modest compared with the periodogram. We tested the influence of the number of tapers used and found that narrow modes at low n values are broadened to the extent that they can no longer be fit if the number of tapers is too large. For helioseismic time series of this length and temporal resolution, the optimal number of tapers is less than 10.

Komm, R. W.↗

Data Access Tools And Services At The Goddard Distributed Active Archive Center (GDAAC)

As one of the largest providers of Earth Science data from the Earth Observing System, GDAAC provides the latest data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Solar Radiation and Climate Experiment (SORCE) data products via GDAAC's data pool (50TB of disk cache). In order to make this huge volume of data more accessible to the public and science communities, the GDAAC offers multiple data access tools and services: Open Source Project for Network Data Access Protocol (OPeNDAP), Grid Analysis and Display System (GrADS/DODS) (GDS), Live Access Server (LAS), OpenGlS Web Map Server (WMS) and Near Archive Data Mining (NADM). The objective is to assist users in retrieving electronically a smaller, usable portion of data for further analysis. The OPeNDAP server, formerly known as the Distributed Oceanographic Data System (DODS), allows the user to retrieve data without worrying about the data format. OPeNDAP is capable of server-side subsetting of HDF, HDF-EOS, netCDF, JGOFS, ASCII, DSP, FITS and binary data formats. The GrADS/DODS server is capable of serving the same data formats as OPeNDAP. GDS has an additional feature of server-side analysis. Users can analyze the data on the server there by decreasing the computational load on their client's system. The LAS is a flexible server that allows user to graphically visualize data on the fly, to request different file formats and to compare variables from distributed locations. Users of LAS have options to use other available graphics viewers such as IDL, Matlab or GrADS. WMS is based on the OPeNDAP for serving geospatial information. WMS supports OpenGlS protocol to provide data in GIs-friendly formats for analysis and visualization. NADM is another access to the GDAAC's data pool. NADM gives users the capability to use a browser to upload their C, FORTRAN or IDL algorithms, test the algorithms, and mine data in the data pool. With NADM, the GDAAC provides an environment physically close to the data source. NADM will benefit users with mining or offer data reduction algorithms by reducing large volumes of data before transmission over the network to the user.

Pham, Long↗

SU-E-J-275: Review - Computerized PET/CT Image Analysis in the Evaluation of Tumor Response to Therapy

Purpose: To review the literature in using computerized PET/CT image analysis for the evaluation of tumor response to therapy. Methods: We reviewed and summarized more than 100 papers that used computerized image analysis techniques for the evaluation of tumor response with PET/CT. This review mainly covered four aspects: image registration, tumor segmentation, image feature extraction, and response evaluation. Results: Although rigid image registration is straightforward, it has been shown to achieve good alignment between baseline and evaluation scans. Deformable image registration has been shown to improve the alignment when complex deformable distortions occur due to tumor shrinkage, weight loss or gain, and motion. Many semi-automatic tumor segmentation methods have been developed on PET. A comparative study revealed benefits of high levels of user interaction with simultaneous visualization of CT images and PET gradients. On CT, semi-automatic methods have been developed for only tumors that show marked difference in CT attenuation between the tumor and the surrounding normal tissues. Quite a few multi-modality segmentation methods have been shown to improve accuracy compared to single-modality algorithms. Advanced PET image features considering spatial information, such as tumor volume, tumor shape, total glycolytic volume, histogram distance, and texture features have been found more informative than the traditional SUVmax for the prediction of tumor response. Advanced CT features, including volumetric, attenuation, morphologic, structure, and texture descriptors, have also been found advantage over the traditional RECIST and WHO criteria in certain tumor types. Predictive models based on machine learning technique have been constructed for correlating selected image features to response. These models showed improved performance compared to current methods using cutoff value of a single measurement for tumor response. Conclusion: This review showed that computerized PET/CT image analysis holds great potential to improve the accuracy in evaluation of tumor response. This work was supported in part by the National Cancer Institute Grant R01CA172638.

60 APPLIED LIFE SCIENCES↗

The Impact of Streaming Data on Sensemaking with Mixed-Initative Visual Analytics

Visual data analysis helps people gain insights into data via interactive visualizations. People generate and test hypotheses and questions about data in context of the domain. This process can generally be referred to as sensemaking. Much of the work on studying sensemaking (and creating visual analytic techniques in support of it) has been focused on static datasets. However, how do the cognitive processes of sensemaking change when data are changing? Further, what implication for design does this create for mixed-initiative visual analytics systems? This paper presents the results of a user study analyzing the impact of streaming data on sensemaking. To perform this study, we developed a mixed-initiative visual analytic prototype, the Streaming Canvas, that affords the analysis of streaming text data. We compare the sensemaking process of people using this tool for a static and streaming dataset. We present the results of this study and discuss the implications on future visual analytic systems that combine machine learning and interactive visualization to help people make sense of streaming data.

visualization↗

Novel Super-Resolution Approach to Time-Resolved Volumetric 4-Dimensional Magnetic Resonance Imaging With High Spatiotemporal Resolution for Multi-Breathing Cycle Motion Assessment

Purpose: To develop and evaluate a super-resolution approach to reconstruct time-resolved 4-dimensional magnetic resonance imaging (TR-4DMRI) with a high spatiotemporal resolution for multi-breathing cycle motion assessment. Methods and Materials: A super-resolution approach was developed to combine fast 3-dimensional (3D) cine MRI with low resolution during free breathing (FB) and high-resolution 3D static MRI during breath hold (BH) using deformable image registration. A T1-weighted, turbo field echo sequence, coronal 3D cine acquisition, partial Fourier approximation, and SENSitivity Encoding parallel acceleration were used. The same MRI pulse sequence, field of view, and acceleration techniques were applied in both FB and BH acquisitions; the intensity-based Demons deformable image registration method was used. Under an institutional review board–approved protocol, 7 volunteers were studied with 3D cine FB scan (voxel size: 5 × 5 × 5 mm{sup 3}) at 2 Hz for 40 seconds and a 3D static BH scan (2 × 2 × 2 mm{sup 3}). To examine the image fidelity of 3D cine and super-resolution TR-4DMRI, a mobile gel phantom with multi-internal targets was scanned at 3 speeds and compared with the 3D static image. Image similarity among 3D cine, 4DMRI, and 3D static was evaluated visually using difference image and quantitatively using voxel intensity correlation and Dice index (phantom only). Multi-breathing-cycle waveforms were extracted and compared in both phantom and volunteer images using the 3D cine as the references. Results: Mild imaging artifacts were found in the 3D cine and TR-4DMRI of the mobile gel phantom with a Dice index of >0.95. Among 7 volunteers, the super-resolution TR-4DMRI yielded high voxel-intensity correlation (0.92 ± 0.05) and low voxel-intensity difference (<0.05). The detected motion differences between TR-4DMRI and 3D cine were −0.2 ± 0.5 mm (phantom) and −0.2 ± 1.9 mm (diaphragms). Conclusion: Super-resolution TR-4DMRI has been reconstructed with adequate temporal (2 Hz) and spatial (2 × 2 × 2 mm{sup 3}) resolutions. Further TR-4DMRI characterization and improvement are necessary before clinical applications. Multi-breathing cycles can be examined, providing patient-specific breathing irregularities and motion statistics for future 4D radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Galaxy morphological classification catalogue of the Dark Energy Survey Year 3 data with convolutional neural networks

ABSTRACT We present in this paper one of the largest galaxy morphological classification catalogues to date, including over 20 million galaxies, using the Dark Energy Survey (DES) Year 3 data based on convolutional neural networks (CNNs). Monochromatic i-band DES images with linear, logarithmic, and gradient scales, matched with debiased visual classifications from the Galaxy Zoo 1 (GZ1) catalogue, are used to train our CNN models. With a training set including bright galaxies (16 ≤ i < 18) at low redshift (z < 0.25), we furthermore investigate the limit of the accuracy of our predictions applied to galaxies at fainter magnitude and at higher redshifts. Our final catalogue covers magnitudes 16 ≤ i < 21, and redshifts z < 1.0, and provides predicted probabilities to two galaxy types – ellipticals and spirals (disc galaxies). Our CNN classifications reveal an accuracy of over 99 per cent for bright galaxies when comparing with the GZ1 classifications (i < 18). For fainter galaxies, the visual classification carried out by three of the co-authors shows that the CNN classifier correctly categorizes discy galaxies with rounder and blurred features, which humans often incorrectly visually classify as ellipticals. As a part of the validation, we carry out one of the largest examinations of non-parametric methods, including ∼100 ,000 galaxies with the same coverage of magnitude and redshift as the training set from our catalogue. We find that the Gini coefficient is the best single parameter discriminator between ellipticals and spirals for this data set.

79 ASTRONOMY AND ASTROPHYSICS↗