Continuous development of nTracer2 and its deployment at NIH image repositories
Continuous development of nTracer2 and its deployment at NIH image repositories
批准号:
10726178
负责人:
Dawen Cai
金额:
$251.57万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-07 至 2026-08-06
关键词:
AdoptionAnatomyBRAIN initiativeBlood VesselsBrainBrain imagingCell NucleusCell modelCellsCellular PhoneCellular StructuresCollaborationsCommunitiesComputer SystemsComputer softwareComputersDataData ScienceData SetDatabasesDegenerative DisorderDepositionDevelopmentDocumentationEcosystemEducational workshopFundingGeneral PopulationGroup MeetingsHigh Performance ComputingHomeImageIndividualInternetLabelLocationMetadataMethodologyMethodsMicroscopyModalityModernizationModificationMolecularMorphologyMusNeuronsNeurosciencesNeurosciences ResearchPerformancePrivatizationPublishingResearchResearch PersonnelResolutionResourcesSeriesServicesSliceSoftware EngineeringSourceStandardizationSynapsesTissuesUnited States National Institutes of HealthVisualizationWorkcell typecloud basedcomputing resourcesdata accessdata formatdata frameworkdata handlingdata managementdata repositorydata resourcedata sharingdata standardsdata submissiondevelopmental diseasefile formatfluorescence imaginghackathonhigh throughput screeningimage archival systemimage visualizationimprovedindexingmachine visionmultimodal datamultimodalityneuralneuroinformaticsneuronal cell bodynovelpublic repositoryreconstructionrepositoryresponsesoftware developmentsupercomputertechnology research and developmentterabytetesting accesstooltranscriptomicsusabilityweb portalworking group
中文摘要
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英文摘要
Abstract
In response to the BRAIN Initiative “Integration and Analysis of BRAIN Initiative Data” FOA, we propose
further developing nTracer2, a cloud-based platform for brain image visualization and neuron tracing in
the web browser. To evaluate nTracer2’s real-world performance, we deployed nTracer2 at the NIH
Brain Image Library (BIL) at the Pittsburgh Supercomputer Center to handle whole mouse brain fMOST
fluorescence image datasets. In a public data access test, up to 50 users across the globe smoothly
explored this dataset simultaneously. In this project, our team will work on four Aims. In Aim 1, we will
establish our novel SISF data framework as a scalable image data standard, which includes creating
better data format conversion tools, compression filters, and documentation for SISF. In Aim 2, we will
continue to develop the nTracer2 (content delivery network) CDN server, which includes upgrading the
data management interface and optimizing the performance of the reconstruction database. In Aim 3,
we will continue to develop the nTracer2 application server, which includes developing user
management tools, optimizing high-performance computing performance for existing brain registration
and machine vision functions, integrating imaging datasets taken by multimodal microscopy modalities,
and expanding its neuroinformatics functions. In Aim 4, we will deploy full-stack nTracer2 at BIL and
integrate CCF-registered multimodal datasets stored at multiple NIH repositories.
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