Suppr超能文献

通过将本体论与分面搜索相结合实现三维神经解剖结构的分面可视化。

Faceted visualization of three dimensional neuroanatomy by combining ontology with faceted search.

机构信息

Memorial Sloan-Kettering Cancer Center, New York, USA,

出版信息

Neuroinformatics. 2014 Apr;12(2):245-59. doi: 10.1007/s12021-013-9202-5.

Abstract

In this work, we present a faceted-search based approach for visualization of anatomy by combining a three dimensional digital atlas with an anatomy ontology. Specifically, our approach provides a drill-down search interface that exposes the relevant pieces of information (obtained by searching the ontology) for a user query. Hence, the user can produce visualizations starting with minimally specified queries. Furthermore, by automatically translating the user queries into the controlled terminology our approach eliminates the need for the user to use controlled terminology. We demonstrate the scalability of our approach using an abdominal atlas and the same ontology. We implemented our visualization tool on the opensource 3D Slicer software. We present results of our visualization approach by combining a modified Foundational Model of Anatomy (FMA) ontology with the Surgical Planning Laboratory (SPL) Brain 3D digital atlas, and geometric models specific to patients computed using the SPL brain tumor dataset.

摘要

在这项工作中,我们提出了一种基于分面搜索的方法,通过将三维数字图谱与解剖本体相结合来可视化解剖结构。具体来说,我们的方法提供了一个向下钻取的搜索界面,为用户查询暴露相关的信息(通过搜索本体获得)。因此,用户可以从最小指定的查询开始生成可视化。此外,通过自动将用户查询转换为受控术语,我们的方法消除了用户使用受控术语的需要。我们使用腹部图谱和相同的本体证明了我们方法的可扩展性。我们在开源 3D Slicer 软件上实现了我们的可视化工具。我们通过将修改后的基础解剖模型 (FMA) 本体与外科计划实验室 (SPL) 大脑 3D 数字图谱相结合,并使用 SPL 脑肿瘤数据集计算特定于患者的几何模型,展示了我们的可视化方法的结果。

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