Continued Development and Maintenance of MriStudio
Continued Development and Maintenance of MriStudio
批准号:
10159312
负责人:
MICHAEL I MILLER
金额:
$36.44万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-01 至 2023-02-28
关键词:
AdoptedAgeAlgorithmsAnatomyArchitectureArchivesAtlasesBedside TestingsBrainBrain MappingChargeClinicalClinical DataCollectionCommunitiesComputer softwareComputersDataData AnalysesDevelopmentDiffusion Magnetic Resonance ImagingDigital Imaging and Communications in MedicineDiseaseEducationEnvironmentFacultyFamilyFunctional Magnetic Resonance ImagingGrantHospitalsImageImage AnalysisInstitutional Review BoardsLanguageLesionLibrariesMagnetic Resonance ImagingMagnetic Resonance SpectroscopyMaintenanceManualsMemoryMethodsPatientsPhysiologicalPredispositionProcessPublicationsQuality ControlReportingResourcesRestRunningScientistServicesSpin LabelsStatistical Data InterpretationStructureSupercomputingSystemTechnologyTestingTranslational ResearchTransplantationUniversitiesUpdateWorkanalysis pipelineapplication programming interfacebasecloud platformcomputerized data processingdata exchangedata qualityfile formatfirewallimage processingimaging Segmentationimprovedinterestlarge scale datamultimodalityonline resourceportabilityprogramssegmentation algorithmsoftware as a servicestatisticstooltractographyweb interfacewhite matter
中文摘要
这笔赠款的目的是支持DtiStudio/MriStudio/的继续开发和维护
MriCloud软件系列,由约翰·霍普金斯大学PI的实验室开发。DtiStudio曾经是
2001年推出,至今仍是最广泛使用的处理扩散张量成像的程序之一
(DTI)数据。MriStudio由DiffeoMap和RoiEditor组成,于2007年推出,提供了一个独特的
可在其中执行尖端脑部绘图和基于图谱的图像分析的环境。2014年,我们
推出了一个全新的软件平台MriCloud,它完全基于云架构,具有Web-
界面(www.mricLoud.org)。该平台不仅集成了DTI/MriStudio提供的所有分析功能,而且
它不仅以自动化的方式提供服务,而且还提供了由云架构实现的新型服务。
两年内,注册用户超过1200人,月处理数据达到8000多个
2017年4月。该平台目前提供四种软件即服务(SaaS)。在这
申请,我们建议将这项服务推广至社区,目标如下:
目标1:通过更新、教育和传播提供持续的用户支持
传播:目前,传播的两个主要渠道是基于网络的资源(手册和视频)
以及每月三天的亲身实践教程。每个辅导班接受5个学院和2个学院的12名申请者。
帮助与会者的程序员。随着DtiStudio/MriStudio/MriCloud的功能扩展,
持续和最新的用户支持是最重要的。
资源更新:我们通过采用最先进的技术和新的地图集来继续更新它们
资源。使用不断变化的文件格式(DICOM和专有)更新数据I/O
核磁共振制造商仍然是必不可少的。
目标2:功能的扩展
添加新服务:我们将继续与合作伙伴合作,整合更多的处理流水线
包括使用FLAIR图像、磁共振波谱和定量的基于结构的损伤负荷分析
磁化率图谱数据。
QC报告:我们将制定并纳入三个级别的检查点,用于定量数据质量控制。
目标3:综合分析平台:一系列磁共振图像分析管道在
同一个云平台提供了进行多模式综合分析的独特机会。我们将发展
结合多种磁共振对比度的解剖和生理特征并确定其独特性的工具
感兴趣的疾病的特征。
目标4:带到床边:这是开发和测试我们的云系统作为平台的探索性目标
翻译研究。
英文摘要
The purpose of this grant is to support the continued development and maintenance of DtiStudio/MriStudio/
MriCloud software family, which was developed at the PIs’ lab in Johns Hopkins University. DtiStudio was
introduced in 2001 and remains one of the most widely used programs to process diffusion tensor imaging
(DTI) data. MriStudio, which consists of DiffeoMap and RoiEditor, was introduced in 2007 and provide a unique
environment in which to perform a cutting-edge brain mapping and atlas-based image analysis. In 2014, we
introduced an entirely new software platform, MriCloud, which is fully based on cloud architecture with a web-
interface (www.mricloud.org). This platform not only integrated all the analysis offered by Dti/MriStudio in a fully
automated manner but also provides new types of services that was made possible by the cloud architecture.
Within two years, it has more than 1,200 registered users and the monthly processed data reached over 8,000
in April, 2017. There are currently four Software-as-a-Service (SaaS) provided in this platform. In this
application, we propose to extend this service to the community through the following aims;
Aim 1: Continued user support through update, education, and dissemination
Dissemination: Currently, two major channels of dissemination are web-based resources (manuals and videos)
and hands-on monthly three-day tutorials. Each tutorial accepts 12 applicants with 5 faculties and two
programmers helping the attendees. As the functionalities of DtiStudio/MriStudio/MriCloud expand, the
continued and most updated user supports is of the highest importance.
Resource update: We continue to update them by incorporating state-of-the-art technologies and new atlas
resources. The update of data I/O with ever-changing file formats (DICOM and proprietary) by the four major
MRI manufactures remains essential.
Aim 2: Extension of the functionality
Addition of new services: We continue to work with our collaborators to incorporate further processing pipelines
including structure-based lesion-load analysis using FLAIR images, MR spectroscopy, and quantitative
susceptibility mapping data.
QC report: We will develop and incorporate three levels of check points for quantitative data quality control.
Aim 3: Integrative analysis platform: The co-existence of an array of MR image analysis pipelines within the
same cloud platform provides a unique opportunity to perform multi-modal integrative analysis. We will develop
tools to combine anatomical and physiological features from multiple MR contrasts and characterize unique
features of a disease of interest.
Aim 4: Bring to bedside: This is an exploratory aim to develop and test our cloud system as a platform for
translational research.
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