ITK-Lung: A Software Framework for Lung Image Processing and Analysis
ITK-Lung: A Software Framework for Lung Image Processing and Analysis
批准号:
9325271
负责人:
JAMES C GEE
金额:
$60.57万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-06-01 至 2021-05-31
关键词:
AddressAdoptedAdvertisementsAlgorithmsAntsAtlasesBasic ScienceBiologicalBiological MarkersClinicalCodeCommunitiesComplementComputational algorithmComputer AnalysisComputer softwareDataData SetDetectionDevelopmentDiagnosisDisease ProgressionDocumentationEducational workshopEmploymentEnvironmental air flowEvaluationGoalsHumanImageImage AnalysisImageryImaging technologyIowaLeadLegal patentLibrariesLobeLungLung diseasesMagnetic Resonance ImagingMethodologyMethodsModalityModernizationMonitorMultimodal ImagingNodulePathway interactionsPatientsPennsylvaniaPerformancePerfusionPositron-Emission TomographyProcessPublicationsPublishingPulmonary PathologyReproductionResearchResearch MethodologyResearch PersonnelResourcesS-nitro-N-acetylpenicillamineScienceScientistShapesSiteSoftware FrameworkSoftware ToolsStructureTechniquesTrainingTreatment outcomeUnited States National Institutes of HealthUniversitiesVirginiaWorkbaseclinical practicecomputing resourcesexperiencegraphical user interfaceimage processingimage registrationimaging Segmentationimaging biomarkerimaging potentialimprovedindexinginnovationinsightinteroperabilitylung developmentlung imaginglung lobeneuroimagingnovelopen dataopen sourcepreventprogramsquantitative imagingrespiratorysoftware developmentsymposiumtask analysistechnological innovationtooltrenduser-friendly
中文摘要
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英文摘要
Summary
The development and proliferation of quantitative image analysis methods have accelerated research
efforts and are having an increasingly significant impact in modern clinical practice. Although the
research utility of these techniques has been amply demonstrated in determining longitudinal and
groupwise trends, they are also becoming increasingly relevant in the clinical setting in providing
biomarkers for aiding patient diagnoses, monitoring disease progression, and determining treatment
outcomes. Increases in the capabilities and accessibility of computational facilities and a corresponding
sophistication in computational algorithms have only made such practices more commonplace.
One of the most significant hurdles for the pulmonary imaging field in adopting more quantitative clinical
practices and exploring additional novel research pathways is the open availability of accurate, robust,
and easy-to-use image analysis tools. This project addresses this important unmet need by bringing
together leading expertise in pulmonary image analysis at the University of Pennsylvania, the University
of Virginia, and the University of Iowa to develop, evaluate, and deploy a critical open-science resource
under community support that would allow access to multi-modality data and tools for processing and
analysis of lung imaging data. Toward this end, a comprehensive image analysis and data package,
denoted as ITK-Lung, will be developed to address the specific needs of the multi-modality pulmonary
imaging community. This first-of-its-kind resource will be enhanced by data- and domain-specific tuning
that will accommodate a variety of user backgrounds and needs. These developments will be evaluated
through their application to real-world use cases representing the state-of-the-science in lung imaging
research. The successful completion of this project will help to fully realize the value of computational
image analysis in pulmonary research and lead to new insight that may open novel ways to treat, cure
and even prevent pulmonary disorders.
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NON-AFFINE REGISTRATION
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批准号:8363498
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资助金额:$1.01万
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SHAPE OPTIMIZING DIFFEOMORPHISMS FOR COMPUTATIONAL BIOLOGY
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资助金额:$2.03万
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财政年份:2011
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批准号:7797545
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资助金额:$26.86万
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依托单位:
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资助金额:$25.31万
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