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A dataset of chest X-ray reports annotated with Spatial Role Labeling annotations

机译:胸部X射线报告的数据集用空间角色标记注释注释

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摘要

In this paper, we present a dataset consisting of 2000 chest X-ray reports (available as part of the Open-i image search platform) annotated with spatial information. The annotation is based on Spatial Role Labeling. The information includes annotating a radiographic finding, its associated anatomical location, any potential diagnosis described in connection to the spatial relation (between finding and location), and any hedging phrase used to describe the certainty level of a finding/diagnosis. All these annotations are identified with reference to a spatial expression (or ) that triggers a spatial relation in a sentence. The spatial roles used to encode the spatial information are , , , and . In total, there are 1962 s (mainly prepositions). There are 2293 s, 2167 s, 455 , and 388 s in the dataset. This annotated dataset can be used for developing automatic approaches targeted toward spatial information extraction from radiology reports which then can be applied to numerous clinical applications. We utilize this dataset to develop deep learning-based methods for automatically extracting the s as well as the associated spatial roles .
机译:在本文中,我们介绍了一个由2000个胸部X射线报告组成的数据集(作为具有空间信息的open-i映像搜索平台的一部分提供的数据集。注释是基于空间角色标记。该信息包括注释射线照相查找,其相关解剖位置,与空间关系中描述的任何潜在诊断(在查找和位置之间),以及用于描述查找/诊断的确定性水平的任何对冲短语。所有这些注释都参考了触发句子中的空间关系的空间表达式(或)识别。用于编码空间信息的空间角色,以及。总共有1962年(主要是介词)。数据集中有2293秒,2167年,455和388秒。该注释的数据集可用于开发针对空间信息提取的自动方法,从放射学报告中可以应用于许多临床应用。我们利用此数据集以开发基于深度的学习方法,以便自动提取S以及相关的空间角色。

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