iCube: A similarity-based data cube for medical images

机译：iCube：用于医学图像的基于相似性的数据立方体

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Issuing analytical (OLAP) similarity queries based on images over data warehouses is a core problem in the medical field, as these queries can allow for the investigation and analysis of health data in decision-making processes. In this paper, we propose iCube, a similarity-based data cube for medical images. iCube is an extended data warehouse that encompasses a dimension table specifically designed to store intrinsic features of images, therefore allowing OLAP similarity queries over images. We also show how to build iCube and how to perform OLAP query processing over images. Comparisons of iCube with the current data warehousing technology aided by a metric access method showed that iCube provided an impressive performance improvement to process OLAP similarity queries over images. iCube performance gain ranged from 43% up to 76.7%.

机译：在数据仓库上基于图像发布分析（OLAP）相似性查询是医学领域的核心问题，因为这些查询可以允许在决策过程中调查和分析健康数据。在本文中，我们提出了iCube，这是一种基于相似度的医学图像数据立方体。 iCube是扩展的数据仓库，其中包含专门设计用于存储图像的固有特征的维度表，因此允许对图像进行OLAP相似性查询。我们还将展示如何构建iCube以及如何对图像执行OLAP查询处理。将iCube与借助度量访问方法辅助的当前数据仓库技术进行的比较表明，iCube在处理图像上的OLAP相似性查询方面提供了令人印象深刻的性能改进。 iCube性能提升范围从43％到76.7％。

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《23rd IEEE International Symposium on Computer-Based Medical Systems》|2010年|p.321-326|共6页
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Annibal Luana P.; Felipe Joaquim C.; Ciferri Cristina D. A.; Ciferri Ricardo R.;
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中图分类基础医学;在其他方面的应用;
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iCube: A similarity-based data cube for medical images

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