Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms.

Published

Journal Article

The purpose of this study was to evaluate image similarity measures employed in an information-theoretic computer-assisted detection (IT-CAD) scheme. The scheme was developed for content-based retrieval and detection of masses in screening mammograms. The study is aimed toward an interactive clinical paradigm where physicians query the proposed IT-CAD scheme on mammographic locations that are either visually suspicious or indicated as suspicious by other cuing CAD systems. The IT-CAD scheme provides an evidence-based, second opinion for query mammographic locations using a knowledge database of mass and normal cases. In this study, eight entropy-based similarity measures were compared with respect to retrieval precision and detection accuracy using a database of 1820 mammographic regions of interest. The IT-CAD scheme was then validated on a separate database for false positive reduction of progressively more challenging visual cues generated by an existing, in-house mass detection system. The study showed that the image similarity measures fall into one of two categories; one category is better suited to the retrieval of semantically similar cases while the second is more effective with knowledge-based decisions regarding the presence of a true mass in the query location. In addition, the IT-CAD scheme yielded a substantial reduction in false-positive detections while maintaining high detection rate for malignant masses.

Full Text

Duke Authors

Cited Authors

  • Tourassi, GD; Harrawood, B; Singh, S; Lo, JY; Floyd, CE

Published Date

  • January 1, 2007

Published In

Volume / Issue

  • 34 / 1

Start / End Page

  • 140 - 150

PubMed ID

  • 17278499

Pubmed Central ID

  • 17278499

International Standard Serial Number (ISSN)

  • 0094-2405

Digital Object Identifier (DOI)

  • 10.1118/1.2401667

Language

  • eng

Conference Location

  • United States