Open microscopy environment

I. Goldberg
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引用次数: 26

Abstract

Summary form only given. The Open Microscopy Environment (OME) is a framework for the management and analysis of image data and metadata in biological microscopy. Biological microscopy images can be collected in many different ways, and may represent many different kinds of information which changes continually with evolving technology and experimental goals. A framework that fully encompasses biological microscopy in scope cannot rely on a fixed data model - it must be designed to accommodate ever-changing informatics needs. The challenge posed by a fluid data model is similar to one addressed by the semantic web, principally support for arbitrary or user-defined semantics and ontologies. However, an analysis framework faces additional challenges besides the management of semantics: definition of analytic units as transforms between semantic constructs, definition of aggregates of analytic units to represent work flows, interfaces to algorithm implementations, and maintenance of data provenance or history. A collaborative scientific environment also demands that these locally defined semantics and transforms be fully transportable for subsequent review or analysis. OME incorporates these components in a database-backed system targeted at end-user biologists. This presentation will briefly describe the various components of OME: the semantic layer (Semantic Types - STs), the analytical un its used to transform between STs (Analysis Modules), the units of work flow (Analysis Chains), the work-flow processor (Analysis Engine), and the transportability layer (OME XML). An example of a complex work flow will also be presented illustrating how this system is used for automated image classification.
开放显微镜环境
只提供摘要形式。开放显微镜环境(OME)是一个用于管理和分析生物显微镜图像数据和元数据的框架。生物显微镜图像可以通过许多不同的方式收集,并且可以代表许多不同种类的信息,这些信息随着技术和实验目标的发展而不断变化。一个完全包含生物显微镜的框架不能依赖于固定的数据模型——它必须被设计成适应不断变化的信息学需求。流动数据模型所面临的挑战与语义web所面临的挑战类似,主要是支持任意或用户定义的语义和本体。然而,除了语义管理之外,分析框架还面临着额外的挑战:将分析单元定义为语义结构之间的转换,定义分析单元的聚合以表示工作流,算法实现的接口,以及数据来源或历史的维护。协作的科学环境还要求这些局部定义的语义和转换完全可用于后续的审查或分析。OME将这些组件整合到针对最终用户生物学家的数据库支持系统中。本演讲将简要介绍OME的各个组成部分:语义层(语义类型- STs)、用于在STs(分析模块)之间转换的分析单元、工作流单元(分析链)、工作流处理器(分析引擎)和可移植性层(OME XML)。还将介绍一个复杂工作流程的示例,说明如何将该系统用于自动图像分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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