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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

An Accelerated Clip Algorithm for Unstructured Meshes: A Batch-Driven Approach

The clip technique is a popular method for visualizing complex structures and phenomena within 3D unstructured meshes. Meshes can be clipped by specifying a scalar isovalue to produce an output unstructured mesh with its external surface as the isovalue. Similar to isocontouring, the clipping process relies on scalar data associated with the mesh points, including scalar data generated by implicit functions such as planes, boxes, and spheres, which facilitates the visualization of results interior to the grid. In this paper, we introduce a novel batch-driven parallel algorithm based on a sequential clip algorithm designed for high-quality results in partial volume extraction. Our algorithm comprises five passes, each progressively processing data to generate the resulting clipped unstructured mesh. The novelty lies in the use of fixed-size batches of points and cells, which enable rapid workload trimming and parallel processing, leading to a significantly improved memory footprint and run-time performance compared to the original version. On a 32-core CPU, the proposed batch-driven parallel algorithm demonstrates a run-time speed-up of up to 32.6x and a memory footprint reduction of up to 4.37x compared to the existing sequential algorithm. The software is currently available under an open-source license in the VTK visualization system.

Tsalikis, Spiros↗
DOE OSTI2023

Evaluation of Portable Programming Models to Accelerate LArTPC Detector Simulations

The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE). Accurately simulating LArTPC detector responses is essential for analysis algorithm development and physics model interpretations. Accurate LArTPC detector response simulations are computationally demanding, and can become a bottleneck in the analysis workflow. Compute devices such as General-Purpose Graphics Processing Units (GPGPUs) have the potential to substantially accelerate simulations compared to traditional CPU-only processing. The software development for these compute accelerators often carries the cost of specialized code refactorization and porting to match the target hardware architecture. With the rapid evolution and increased diversity of the computer architecture landscape, it is highly desirable to have a portable solution that also maintains reasonable performance. We report our ongoing effort in evaluating Kokkos as a basis for this portable programming model using LArTPC simulations in the context of the Wire-Cell Toolkit, a C++ library for LArTPC simulations, data analysis, reconstruction and visualization.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Havery Mudd 2014-2015 Computer Science Conduit Clinic. Final Report

Conduit, a new open-source library developed at Lawrence Livermore National Laboratories, provides a C++ application programming interface (API) to describe and access scientific data. Conduit’s primary use is for inmemory data exchange in high performance computing (HPC) applications. Our team tested and improved Conduit to make it more appealing to potential adopters in the HPC community. We extended Conduit’s capabilities by prototyping four libraries: one for parallel communication using MPI, one for I/O functionality, one for aggregating performance data, and one for data visualization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Proceedings of the 1998 International Computational Accelerator Physics Conference

The 1998 International Computational Accelerator Physics Conference, ICAP’98, was held September 14-18, 1998, at the Monterey Convention Center in Monterey, California. The meeting continued the tradition of four earlier Computational Accelerator Physics conferences, held in La Jolla, California (1988), Los Alamos, New Mexico (1990), Pleasanton, California (1993), and Williamsburg, Virginia (1996). ICAP’98 was organized by the Stanford Linear Accelerator Center (SLAC), Los Alamos National Laboratory (LANL), and the National Energy Research Scientific Computing Center (NERSC), and received support from the U.S. Department of Energy. The aim of this conference series is to discuss recent advances in Computational Accelerator Physics and their applications to solving important problems related to present and future accelerators. The ICAP’98 program included plenary sessions on modeling challenges in next-generation accelerators, state-of-the art methods in computational accelerator physics, and a view of what high-end computing would be like in the 21st century. There were also focused sessions on accelerator design and control, modeling high intensity beam phenomena, electromagnetic modeling, advanced algorithms, software environments and libraries, visualization and graphic interfaces, modeling advanced accelerator concepts, modeling the beam-beam interaction, computing wakefields, and combined particle/field simulations. In addition to these oral sessions there was a poster session and a vendor display. Prior to the start of the technical program, a half-day tutorial on High Performance Computing was hosted by NERSC. The ICAP series recognizes that computing and, in particular, advanced computing, is playing an increasingly important role in the successful design and development of major accelerator facilities, and in research and development leading to advances in accelerator technology. We expect that this new emphasis on high-end computing will continue in future ICAP conferences.

Ko, Kwok↗
DOE OSTI2025

FY25 MOOSE Usability Improvements: 3D Meshing Capabilities, Initiation of Geometry Support for Monte Carlo Tools, and Enhancement of MOOSE/Workbench User Input Interactions

Usability improvements have been made to MOOSE and Workbench in FY25 to enhance usability and user workflows. Assorted enhancement have been made to MOOSE’s intrinsic meshing capabilities in order to enable more flexible and complex meshing of nuclear reactor systems, in particular for 3D applications. Mesh generators have been added to perform operations such as batch mesh generation, surface mesh generation, and creation of 3D transition layers. These mesh generation capabilities make it much easier to generate high quality non-extruded 3D meshes. Additionally, work to integrate Monte Carlo reactor physics simulations into MOOSE-based multi-physics workflows has reached another milestone with the implementation of the Constructive Solid Geometry (CSG) base framework. This framework lays the foundation for mesh generators to offer the user a generic CSG output option (as opposed to a finite element mesh). To support users, workshop on the MOOSE Reactor Module was delivered which featured hands-on examples using the NEAMS Workbench on INL’s High Performance Computing system. Recent updates to the NEAMS Workbench, WASP, and the MOOSE language server have introduced several improvements aimed at making MOOSE-based simulation setup and input management faster, more accurate, and easier to use. Key capabilities that have been added include multi-tab-stop autocompletion, visual input diagnostics, developer-directed data visualizations, upgraded ParaView integration, and Workspace-level file tracking. Together, these changes make it easier for users to build, validate, and manage complex MOOSE-based simulation models — especially those involving reusable components, included files, and datasets. The improvements are designed to save time, reduce input errors, and help users get to a successful simulation run faster, with more confidence in the results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

A geospatial risk analysis graphical user interface for identifying hazardous chemical emission sources

Background: Performing back trajectory and forward trajectory using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) is a reliable approach for assessing particle transport after release among mid-field atmospheric models. HYSPLIT has an externally facing online interface that allows non-expert users to run the model trajectories without requiring extensive training or programming. However, the existing HYSPLIT interface is limited if simulations have a large amount of meteorological data and timesteps that are not coincident. The objective of this study is to design and develop a more robust tool to rapidly evaluate hazard transport conditions and to perform risk analysis, while still maintaining an intuitive and user-friendly interface. Methods: HYSPLIT calculates forward and backward trajectories of particles based on wind speed, wind direction, and the corresponding location, timestamp, and Pasquill stability classes of the regions of the atmosphere in terms of the wind speed, the amount of solar radiation, and the fractional cloud cover. The computed particle transport trajectories, combined with the online Proton Transfer Reaction-Mass Spectrometry (PTR-MS) data (https://figshare.com/articles/dataset/ARL_Data_from_PROS_station_at_Hanford_site/19993964), can be used to identify and quantify the sources and affected area of the hazardous chemicals’ emission using the potential source distribution function (PSDF). PSDF is an improved statistical function based on the well-known potential source contribution function (PSCF) in establishing the air pollutant source and receptor relationship. Performing this analysis requires a range of meteorological and pollutant concentration measurements to be statistically meaningful. The existing HYSPLIT graphical user interface (GUI) does not easily permit computations of trajectories of a dataset of meteorological data in high temporal frequency. To improve the performance of HYSPLIT computations from a large dataset and enhance risk analysis of the accidental release of material at risk, a geospatial risk analysis tool (GRAT-GUI) is created to allow large data sets to be processed instantaneously and to provide ease of visualization. Results: The GRAT-GUI is a native desktop-based application and can be run in any Windows 10 system without any internet access requirements, thus providing a secure way to process large meteorological datasets even on a standalone computer. GRAT-GUI has features to import, integrate, and convert meteorological data with various formats for hazardous chemical emission source identification and risk analysis as a self-explanatory user interface. The tool is available at https://figshare.com/articles/software/GRAT/19426742.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Evaluation of Portable Programming Models to Accelerate LArTPC Detector Simulations

The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE). Accurately simulating LArTPC detector responses is essential for analysis algorithm development and physics model interpretations. Accurate LArTPC detector response simulations are computationally demanding, and can become a bottleneck in the analysis workflow. Compute devices such as General-Purpose Graphics Processing Units (GPGPUs) have the potential to substantially accelerate simulations compared to traditional CPU-only processing. The software development that requires often carries the cost of specialized code refactorization and porting to match the target hardware architecture. With the rapid evolution and increased diversity of the computer architecture landscape, it is highly desirable to have a portable solution that also maintains reasonable performance. We report our ongoing effort in evaluating Kokkos as a basis for this portable programming model using LArTPC simulations in the context of the Wire-Cell Toolkit, a C++ library for LArTPC simulations, data analysis, reconstruction and visualization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Performance analysis and data reduction for exascale scientific workflows

Chimbuko is the first in situ, scalable, workflow-level performance analysis tool for trace-level analysis and visualization of application performance. This tool was developed by the Co-design Center for Online Data Analysis and Reduction and funded by the U.S. Department of Energy’s Exascale Computing Project. We provide a detailed description of Chimbuko’s architecture and illustrate our online and offline visualization with multiple use cases. We also present results for the deployment and scalability of the tool as applied to a high-energy physics workflow running at large scale on the Frontier supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Final Report on MEGAPIE Target Irradiation and Post-Irradiation Examination

Megawatt pilot experiment (MEGAPIE) was successfully performed in 2006. One of the important goals of MEGAPIE is to understand the behaviour of structural materials of the target components exposed to high fluxes of high-energy protons and spallation neutrons in flowing LBE (liquid lead-bismuth eutectic) environment by conducting post-irradiation examination (PIE). The PIE includes four major parts: non-destructive test, radiochemical analysis of production and distribution of radionuclides produced by spallation reaction in LBE, analysis of LBE corrosion effects on structural materials, T91 and SS 316L steels, and mechanical testing of the T91 and SS 316L steels irradiated in the lower part of the target. The non-destructive test (NDT) including visual inspection and ultrasonic measurement was performed in the proton beam window area of the T91 calotte of the LBE container, the most intensively irradiated part of the MEGAPIE target. The visual inspection showed no visible failure and the ultrasonic measurement demonstrated no detectable change in thickness in the beam window area. Gamma mapping was also performed in the proton beam window area of the AlMg 3 safety-container. The gamma mapping results were used to evaluate the accumulated proton fluence distribution profile, the input data for determining irradiation parameters. Radiochemical analysis of radionuclides produced by spallation reaction in LBE is to improve the understanding of the production and distribution of radionuclides in the target. The results demonstrate that the radionuclides of noble metals, 207 Bi, 194 Hg/Au are rather homogeneously distributed within the target, while radionuclides of electropositive elements are found to be deposited on the steel-LBE interface. The corrosion effect of LBE on the structural components under intensive irradiation was investigated by metallography. The results show that no evident corrosion damages. However, unexpected deep cracks were found in the EBW (electron beam weld) of the LBE container in the intensive irradiation zone of the target, which should be formed during irradiation. In the SS 316L steel of the flow guide tube, inclusions or precipitates enriched with O, Si, S, Ca, Ti and Mn were observed. Many of them are very long, up to a few mm, and located on grain boundaries along the extrusion direction of the tube. The degradation of the mechanical properties of the T91 and SS 316L steels has been investigated by conducting tensile tests on the specimens extracted from the T91 and SS 316L components in the intensive irradiation region. The results obtained from the proton beam window of the T91 calotte exhibit a good ductility of T91 steel after irradiation at 6-7 dpa (displacement per atom) in contact with flowing LBE.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Exploration of high-dimensional scalar function for nuclear reactor safety analysis and visualization

The next generation of methodologies for nuclear reactor Probabilistic Risk Assessment (PRA) explicitly accounts for the time element in modeling the probabilistic system evolution and uses numerical simulation tools to account for possible dependencies between failure events. The Monte-Carlo (MC) and the Dynamic Event Tree (DET) approaches belong to this new class of dynamic PRA methodologies. A challenge of dynamic PRA algorithms is the large amount of data they produce which may be difficult to visualize and analyze in order to extract useful information. We present a software tool that is designed to address these goals. We model a large-scale nuclear simulation dataset as a high-dimensional scalar function defined over a discrete sample of the domain. First, we provide structural analysis of such a function at multiple scales and provide insight into the relationship between the input parameters and the output. Second, we enable exploratory analysis for users, where we help the users to differentiate features from noise through multi-scale analysis on an interactive platform, based on domain knowledge and data characterization. Our analysis is performed by exploiting the topological and geometric properties of the domain, building statistical models based on its topological segmentations and providing interactive visual interfaces to facilitate such explorations. We provide a user's guide to our software tool by highlighting its analysis and visualization capabilities, along with a use case involving data from a nuclear reactor safety simulation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Deployment of Performance Management Methodology as part of Liquid Waste Program at Savannah River Site - 12178

In 2009, Savannah River Remediation LLC (SRR) assumed the management lead of the Liquid Waste (LW) Program at the Savannah River Site (SRS). The four SRR partners and AREVA, as an integrated subcontractor are performing the ongoing effort to safely and reliably: - Close High Level Waste (HLW) storage tanks; - Maximize waste throughput at the Defense Waste Processing Facility (DWPF); - Process salt waste into stable final waste form; - Manage the HLW liquid waste material stored at SRS. As part of these initiatives, SRR and AREVA deployed a performance management methodology based on Overall Equipment Effectiveness (OEE) at the DWPF in order to support the required production increase. This project took advantage of lessons learned by AREVA through the deployment of Total Productive Maintenance and Visual Management methodologies at the La Hague reprocessing facility in France. The project also took advantage of measurement data collected from different steps of the DWPF process by the SRR team (Melter Engineering, Chemical Process Engineering, Laboratory Operations, Plant Operations). Today the SRR team has a standard method for measuring processing time throughout the facility, a reliable source of objective data for use in decision-making at all levels, and a better balance between engineering department goals and operational goals. Preliminary results show that the deployment of this performance management methodology to the LW program at SRS has already significantly contributed to the DWPF throughput increases and is being deployed in the Saltstone facility. As part of the liquid waste program on Savannah River Site, SRR committed to enhance production throughput of DWPF. Beyond technical modifications implemented at different location of the facility, SRR deployed performance management methodology based on OEE metrics. The implementation benefited from the experience gained by AREVA in its own facilities in France. OEE proved to be a valuable tool in order to support the enhancement program in DWPF by providing unified metrics to measure plant performances, identify bottleneck location, and rank the most time consuming causes from objective data shared between the different groups belonging to the organization. Beyond OEE, the Visual Management tool adapted from the one used at La Hague were also provided in order to further enhance communication within the operating teams. As a result of all the initiatives implemented on DWPF, achieved production has been increased to record rates from FY10 to FY11. It is expected that thanks to the performance management tools now available within DWPF, these results will be sustained and even improved in the future to meet system plan targets. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Final Report Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

The primary challenge motivating this project is the widening gap between the ability to compute information and to store it for subsequent analysis. This gap adversely impacts science code teams, who can perform analysis only on a small fraction of the data they calculate, resulting in the substantial likelihood of lost or missed science, when results are computed but not analyzed. Our approach is to perform as much analysis or visualization processing on data while it is still resident in memory, which is known as in situ processing. The idea in situ processing was not new at the time of the start of this effort in 2014, but efforts in that space were largely ad hoc, and there was no concerted effort within the research community that aimed to foster production-quality software tools suitable for use by Department of Energy (DOE) science projects. Our objective was to produce and enable the use of production-quality in situ methods and infrastructure, at scale, on DOE high-performance computing (HPC) facilities, though we expected to have an impact beyond DOE due to the widespread nature of the challenges, which affect virtually all large-scale computational science efforts. To achieve this objective, we engaged in software technology research and development (R&D), in close partnerships with DOE science code teams, to produce software technologies that were shown to run efficiently at scale on DOE HPC platforms.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

I/O in Machine Learning Applications on HPC Systems: A 360-degree Survey

Growing interest in Artificial Intelligence (AI) has resulted in a surge in demand for faster methods of Machine Learning (ML) model training and inference. This demand for speed has prompted the use of high performance computing (HPC) systems that excel in managing distributed workloads. Because data is the main fuel for AI applications, the performance of the storage and I/O subsystem of HPC systems is critical. In the past, HPC applications accessed large portions of data written by simulations or experiments or ingested data for visualizations or analysis tasks. ML workloads perform small reads spread across a large number of random files. This shift of I/O access patterns poses several challenges to modern parallel storage systems. In this paper, we survey I/O in ML applications on HPC systems, and target literature within a 6-year time window from 2019 to 2024. We define the scope of the survey, provide an overview of the common phases of ML, review available profilers and benchmarks, examine the I/O patterns encountered during offline data preparation, training, and inference, and explore I/O optimizations utilized in modern ML frameworks and proposed in recent literature. Lastly, we seek to expose research gaps that could spawn further R&D.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The Sensor Dilemma in Intelligent Transportation Systems

Intelligent Transportation Systems (ITS) are at the forefront in advancing the way we interact and perceive with the transportation network. This revolution is fueled by the significant advancement in sensor perception technologies such as Radar, LiDAR and Video Imaging which are the most popular modalities for ITS. Real-time perception data from these sensors allows intelligent infrastructure side decision making to improve the energy, efficiency and safety at traffic intersections. As traffic departments across the United States are transitioning from traditional loop detectors / emulators and embracing newer technologies, they are often left with a dilemma in choosing a sensor technology for infrastructure-based perception which is reliable, inexpensive, easy to setup and has robust performance in varying weather conditions. However, choosing a sensor which checks all boxes is not straightforward as every sensor type has unique benefits and drawbacks. Radar is excellent at detecting long range vehicles and weather resistance but lacks high resolution. LiDAR is expensive and weather-sensitive, while cameras provide rich visual data at a low cost but are constrained by lighting and visibility. This study examines Radar, LiDAR and camera sensors capabilities to ascertain whether any of these qualifies as the "best" sensor for ITS perception. Through this evaluation, we hope to draw attention to the necessity of National Renewable Energy Laboratory's (NREL) Infrastructure Perception and Control (IPC) framework which presents a multi-sensor track data fusion engine to assimilate multiple data streams in order to provide robust and reliable perception. While no single sensor can meet all the demands of ITS, a hybrid approach combining multiple sensor modalities like Radar, LiDAR and cameras, offers the most robust solution for enhancing the safety and efficiency in intelligent transportation systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

A High-Quality Workflow for Multi-Resolution Scientific Data Reduction and Visualization

Multi-resolution methods such as Adaptive Mesh Refinement (AMR) can enhance storage efficiency for HPC applications generating vast volumes of data. However, their applicability is limited and cannot be universally deployed across all applications. Furthermore, integrating lossy compression with multi-resolution techniques to further boost storage efficiency encounters significant barriers. To this end, we introduce an innovative workflow that facilitates high-quality multi-resolution data compression for both uniform and AMR simulations. Initially, to extend the usability of multi-resolution techniques, our workflow employs a compression-oriented Region of Interest (ROI) extraction method, transforming uniform data into a multi-resolution format. Subsequently, to bridge the gap between multi-resolution techniques and lossy compressors, we optimize three distinct compressors, ensuring their optimal performance on multi-resolution data. These optimizations can improve the compression ratio of SOTA approaches by up to 3.3× under the same data quality loss. Lastly, we incorporate an advanced uncertainty visualization method into our workflow to understand the potential impacts of lossy compression. Experimental evaluation demonstrates that our workflow achieves significant compression quality improvements.

Wang, Daoce↗
DOE OSTI2013

High spatial resolution brain functional MRI using submillimeter balanced steady-state free precession acquisition

Purpose: One of the technical advantages of functional magnetic resonance imaging (fMRI) is its precise localization of changes from neuronal activities. While current practice of fMRI acquisition at voxel size around 3 × 3 × 3 mm{sup 3} achieves satisfactory results in studies of basic brain functions, higher spatial resolution is required in order to resolve finer cortical structures. This study investigated spatial resolution effects on brain fMRI experiments using balanced steady-state free precession (bSSFP) imaging with 0.37 mm{sup 3} voxel volume at 3.0 T. Methods: In fMRI experiments, full and unilateral visual field 5 Hz flashing checkerboard stimulations were given to healthy subjects. The bSSFP imaging experiments were performed at three different frequency offsets to widen the coverage, with functional activations in the primary visual cortex analyzed using the general linear model. Variations of the spatial resolution were achieved by removing outerk-space data components. Results: Results show that a reduction in voxel volume from 3.44 × 3.44 × 2 mm{sup 3} to 0.43 × 0.43 × 2 mm{sup 3} has resulted in an increase of the functional activation signals from (7.7 ± 1.7)% to (20.9 ± 2.0)% at 3.0 T, despite of the threefold SNR decreases in the original images, leading to nearly invariant functional contrast-to-noise ratios (fCNR) even at high spatial resolution. Activation signals aligning nicely with gray matter sulci at high spatial resolution would, on the other hand, have possibly been mistaken as noise at low spatial resolution. Conclusions: It is concluded that the bSSFP sequence is a plausible technique for fMRI investigations at submillimeter voxel widths without compromising fCNR. The reduction of partial volume averaging with nonactivated brain tissues to retain fCNR is uniquely suitable for high spatial resolution applications such as the resolving of columnar organization in the brain.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Improving Positioning in High-Dose Radiotherapy for Prostate Cancer: Safety and Visibility of Frequently Used Gold Fiducial Markers

Purpose: The use of gold fiducial markers (GFMs) for prostate positioning in high-dose radiotherapy is gaining interest. The purpose of this study was to compare five GFMs regarding feasibility of ultrasound-based implantation in the prostate and intraprostatic lesion (IPL); toxicity; visibility on transabdominal ultrasound (TU) and cone-beam CT (CBCT); reliability of automatic, soft tissue, and GFM-based CBCT patient positioning by comparing manual and automatic fusion CBCT. Methods and Materials: Twenty-five patients were included. Pain and toxicity were scored after implantation and high-dose radiotherapy. Fisher exact test was used to evaluate the correlation of patients' characteristics and prostatitis. Positioning was evaluated on TU and kilovoltage CBCT images. CBCT fusion was performed automatically (Elekta XVI technology, release 3.5.1 b27, based on grey values) and manually on soft tissue and GFMs. Pearson correlation statistics and Bland-Altman evaluation were used. Five GFMs were compared. Results: Twenty percent of the patients developed prostatitis despite antibiotic prophylaxis. Cigarette smoking was significantly correlated with prostatitis. The visualization of all GFMs on TU was disappointing. Consequently we cannot recommend the use of these GFMs for TU-based prostate positioning. For all GFMs, there was only fair to poor linear correlation between automatic and manual CBCT images, indicating that even when GFMs are used, an operator evaluation is imperative. However, when GFMs were analyzed individually, a moderate to very strong correlation between automatic and manual positioning was found for larger GFMs in all directions. Conclusion: The incidence of prostatitis in our series was high. Further research is imperative to define the ideal preparation protocol preimplantation and to select patients. Automatic fusion is more reliable with larger GFMs at the cost of more scatter. The stability of all GFMs was proven.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Design of a graphical user interface for few-shot machine learning classification of electron microscopy data

The recent growth in data generation by modern electron microscopes requires rapid, scalable, and flexible approaches to image segmentation and analysis. Few-shot machine learning, which can richly classify images from a handful of user-provided examples, is a promising route to high-throughput analysis. However, current command-line implementations of such approaches can be slow and unintuitive to use, lacking the real-time feedback necessary to perform effective classification. Here we report on the development of a Python-based graphical user interface that enables end users to easily conduct and visualize the output of few-shot learning models. This interface is portable and can be hosted locally or on the web, providing the opportunity to reproducibly conduct, share, and crowd-source few-shot analyses.

97 MATHEMATICS AND COMPUTING↗