AFINITI - An Augmented System for Neuroimaging Followup
AFINITI - An Augmented System for Neuroimaging Followup
批准号:
7918574
负责人:
STEPHEN TC WONG
金额:
$7.2万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-30 至 2010-09-29
关键词:
AlgorithmsArchivesBiomedical ResearchBrainBrain imagingClinicalClinical ResearchCommunitiesComputational algorithmComputer AssistedComputer softwareDataData SourcesDatabasesDecision MakingDevelopmentDiagnosisEducationEngineeringEnvironmentFederal GovernmentFollow-Up StudiesFutureGoalsGuidelinesHealth Insurance Portability and Accountability ActHospitalsHydrocephalusImageImage AnalysisImageryInformation ServicesInformation SystemsInstitutionLifeMagnetic Resonance ImagingMedical ImagingMetastatic malignant neoplasm to brainMethodsMonitorPatientsPhysiciansPicture Archiving and Communication SystemPrimary Brain NeoplasmsProcessPublic HealthQualifyingRegulationReportingResearchResearch Ethics CommitteesResearch PersonnelSystemTechniquesTherapeuticTherapeutic InterventionTranslatingWomanbasebiomedical informaticsclinical careclinical practicecomputerizedcomputerized data processingdata integrationdesigndiagnostic accuracyfollow-upimage processingimaging informaticsinsightinterestmedical schoolsmultimodalitynervous system disorderneuroimagingopen sourcepatient privacyprototyperesponsesystem architecturetherapy designtooltreatment response
中文摘要
描述(由申请人提供):
定量图像处理用于纵向神经成像随访的研究已经报道了二十多年。许多脑图像处理和分析的算法和方法已经被报道、验证和免费获得,但很少有被设计用于实际临床和研究用途或集成到临床信息系统中。这严重限制了医学影像研究界开发的计算算法和方法对临床神经影像实践和基于神经影像的临床研究的影响。
我们建议将现有的经过验证的神经影像分析工具整合到图像信息学系统AFINITI(治疗干预的神经影像辅助跟踪)中,旨在通过为口译和转诊医生提供精确、可重复的、定量评估脑图像纵向变化所需的自动化工具和增强信息,来提高诊断准确性并减少解释神经成像后续研究的错误,以便在几种常见情况下进行治疗干预的纵向跟踪。主要目标是将生物医学信息学研究产生的工具和技术转化为实际的临床环境,用于诊断、治疗决策、治疗反应监测、临床教育和神经系统疾病研究。
AFINITI系统将被开发、评估并应用于临床工作流程,并在布里格姆妇女医院-哈佛医学院(BWH-HMS)临床神经放射科和BWH-HMS朗伍德磁共振研究中心(LMRC)进行验证。我们将把经过验证的软件打包到一个软件工具包中,并在开源环境中分发它,与流行的医学成像平台兼容,如VTK(可视化工具包)、ITK(洞察工具包)和3D-Slicer。该NeuroImage数据库的数据集成方法和数据库模式也将向公众开放。AFINITI系统架构和组件将形成未来在其他成像中心开发临床成像随访系统的原型。这将是对公众健康的重大贡献。
英文摘要
DESCRIPTION (provided by applicant):
Studies of quantitative image processing for longitudinal neuroimaging followup have been reported for more than two decades. Many algorithms and methods of brain image processing and analysis have been reported, validated and are freely available, but very few have been engineered for practical clinical and research use or integrated into clinical information systems. This has seriously limited the impact that computational algorithms and methods developed by the medical imaging research community have made on clinical neuroimaging practice and neuroimaging based clinical research.
We propose to integrate available validated neuroimage analysis tools into an image informatics system AFINITI (Assisted Followup in Neuroimaging of Therapeutic Intervention), designed to enhance diagnostic accuracy and reduce error in the interpretation of neuroimaging followup studies for longitudinal followup of therapeutic intervention in several common conditions, by providing the interpreting and referring physicians with automated tools and augmented information needed for precise, reproducible, quantitative assessment of longitudinal change in brain images. The primary goal is to translate tools and techniques produced by biomedical informatics research into an actual clinical setting where it can be used in diagnosis, therapeutic decision making, treatment response monitoring, clinical education and research in neurological disease.
The AFINITI system will be developed, evaluated, and implemented into the clinical workflow and validated in Brigham and Women's Hospital-Harvard Medical School (BWH-HMS) clinical neuroradiology section and the BWH-HMS Longwood MRI Research Center (LMRC). We will package the validated software into a software toolkit and distribute it in an open source environment, compatible with popular medical imaging platforms, such as VTK (Visualization Toolkit), ITK (Insight Toolkit), and 3D-Slicer.The data integration method and database schemas for this neuroimage database will also be made available to public. AFINITI system architecture and components will form a prototype for the development of future clinical imaging followup systems in other imaging centers. This will be a substantial contribution to the public health.
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DOI:
10.1016/j.compmedimag.2009.04.006
发表时间:
2009-09
期刊:
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
影响因子:
5.7
作者:
[Nie, Jingxin, Xue, Zhong, Liu, Tianming, Young, Geoffrey S., Setayesh, Kian, Guo, Lei, Wong, Stephen T. C.]
通讯作者:
Wong, Stephen T. C.
DOI:
10.1016/j.compmedimag.2010.07.008
发表时间:
2011-04
期刊:
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
影响因子:
5.7
作者:
[Li, Hai, Xue, Zhong, Cui, Kemi, Wong, Stephen T. C.]
通讯作者:
Wong, Stephen T. C.
DOI:
10.1016/j.acra.2012.03.026
发表时间:
2012-08
期刊:
ACADEMIC RADIOLOGY
影响因子:
4.8
作者:
[Zhu, Ying, Young, Geoffrey S., Xue, Zhong, Huang, Raymond Y., You, Hui, Setayesh, Klan, Hatabu, Hiroto, Cao, Fei, Wong, Stephen T.]
通讯作者:
Wong, Stephen T.
DOI:
10.1016/j.compmedimag.2009.05.007
发表时间:
2010-01
期刊:
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
影响因子:
5.7
作者:
[Xue, Zhong, Wong, Kelvin, Wong, Stephen T. C.]
通讯作者:
Wong, Stephen T. C.
DOI:
10.1002/jmri.22432
发表时间:
2011-02
期刊:
JOURNAL OF MAGNETIC RESONANCE IMAGING
影响因子:
4.4
作者:
[Hu, Xintao, Wong, Kelvin K., Young, Geoffrey S., Guo, Lei, Wong, Stephen T.]
通讯作者:
Wong, Stephen T.
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