Unified framework for fast exact and approximate search in dissimilarity spaces
ACM Transactions on Database Systems (TODS)
Improving feature extraction methods for CT texture analysis
CGIM '07 Proceedings of the Ninth IASTED International Conference on Computer Graphics and Imaging
On nonmetric similarity search problems in complex domains
ACM Computing Surveys (CSUR)
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In this paper we propose a Content-Based Image Retrieval (CBIR) system for retrieval of normal anatomical regions present in Co mputed Tomography (CT) studies of the chest and abdomen. We implement and compare eight similarity measures using local and global co-occurrence texture descriptors. The preliminary results are obtained using a CT database consisting of 344 CT images representing the segmented heart and great vessels, liver, renal and splenic parenchyma, and backbone from two different patients. We evaluate the results with respect to the retrieval precision metric for each of the similarity measures when calculated per organ and overall.