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Design and applications of a multimodality image data warehouse framework.

机译:多模式图像数据仓库框架的设计和应用。

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摘要

A comprehensive data warehouse framework is needed, which encompasses imaging and non-imaging information in supporting disease management and research. The authors propose such a framework, describe general design principles and system architecture, and illustrate a multimodality neuroimaging data warehouse system implemented for clinical epilepsy research. The data warehouse system is built on top of a picture archiving and communication system (PACS) environment and applies an iterative object-oriented analysis and design (OOAD) approach and recognized data interface and design standards. The implementation is based on a Java CORBA (Common Object Request Broker Architecture) and Web-based architecture that separates the graphical user interface presentation, data warehouse business services, data staging area, and backend source systems into distinct software layers. To illustrate the practicality of the data warehouse system, the authors describe two distinct biomedical applications--namely, clinical diagnostic workup of multimodality neuroimaging cases and research data analysis and decision threshold on seizure foci lateralization. The image data warehouse framework can be modified and generalized for new application domains.
机译:需要一个全面的数据仓库框架,其中包括支持疾病管理和研究的影像和非影像信息。作者提出了这样的框架,描述了一般的设计原理和系统架构,并说明了用于临床癫痫研究的多模态神经影像数据仓库系统。数据仓库系统建立在图片存档和通信系统(PACS)环境之上,并应用迭代的面向对象的分析和设计(OOAD)方法以及公认的数据接口和设计标准。该实现基于Java CORBA(通用对象请求代理体系结构)和基于Web的体系结构,该体系结构将图形用户界面表示,数据仓库业务服务,数据暂存区和后端源系统划分为不同的软件层。为了说明数据仓库系统的实用性,作者描述了两种不同的生物医学应用程序:即多模态神经影像学病例的临床诊断研究以及癫痫病灶偏侧化的研究数据分析和决策阈值。图像数据仓库框架可以针对新的应用程序域进行修改和通用化。

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