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Annotating scientific images: a concept-based approach

机译:注释科学图像:基于概念的方法

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摘要

Data annotations are an important kind of metadata that occur in the form of externally assigned descriptions of particular features in Web accessible documents. Such metadata are eventually used in data retrieval tasks on heterogeneous, possible distributed Web- accessible documents. In this paper, we present the model and realization of an annotation framework that scientists can employ to semantically enrich different types of documents, primarily scientific images made available through an image respository. Although we employ ontology like structures, called concepts, for metadata schemes used in annotations, our primary focus is on how concepts are actually used to annotate images and regions of interest, respectively, that exhibit features of interest to a researcher. It turns out that the combined consideration of domain specific concepts and annotated regions in images provides interesting means to analyze the usage of metadata regarding certain correctness and plausibility criteria. We detail our annotation management framework in the context of the Human Brain Project in which Neuroscientists record their observations on specific brain structures, and share and exchange information through concept-based annotations associated with images.
机译:数据注释是一种重要的元数据,以Web可访问文档中的特定功能的外部分配描述的形式发生。这种元数据最终用于异构,可能的分布式网络可访问文档的数据检索任务。在本文中,我们提出了一个注解框架,科学家可以利用语义上富集不同类型的文档的模型和实现,主要是科学的图像通过图像程序存储库提供。虽然我们使用称为概念的结构等本体,但对于注释中使用的元数据方案,我们的主要焦点是如何分别概念用于注释对研究人员感兴趣的特征的概念和地区的概念。事实证明,图像中域特定概念和注释区域的联合考虑提供了分析了对某些正确性和合理性标准的元数据的使用。我们在人脑项目的背景下详述了我们的注释管理框架,其中神经科学家通过与图像相关的基于概念的注释来记录他们对特定脑结构的观察,并交换和交换信息。

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