ICube: A similarity-based data cube for medical images

Conference PaperinProceedings of the IEEE Symposium on Computer-Based Medical Systems · October 2010with22 Reads
DOI: 10.1109/CBMS.2010.6042663 · Source: DBLP
Conference: IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS 2010), Perth, Australia, October 12-15, 2010
Abstract

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 decisionmaking 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 impre ssive performance improvement to process OLAP similarity queries over images. iCube performance gain ranged from 43% up to 76.7%.