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

Publication ,  Journal Article
Tourassi, GD; Harrawood, B; Singh, S; Lo, JY; Floyd, CE
Published in: Med Phys
January 2007

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.

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Published In

Med Phys

DOI

ISSN

0094-2405

Publication Date

January 2007

Volume

34

Issue

1

Start / End Page

140 / 150

Location

United States

Related Subject Headings

  • Subtraction Technique
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Radiographic Image Interpretation, Computer-Assisted
  • Radiographic Image Enhancement
  • Pattern Recognition, Automated
  • Nuclear Medicine & Medical Imaging
  • Mammography
  • Information Theory
  • Information Storage and Retrieval
 

Citation

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Tourassi, G. D., Harrawood, B., Singh, S., Lo, J. Y., & Floyd, C. E. (2007). Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms. Med Phys, 34(1), 140–150. https://doi.org/10.1118/1.2401667
Tourassi, Georgia D., Brian Harrawood, Swatee Singh, Joseph Y. Lo, and Carey E. Floyd. “Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms.Med Phys 34, no. 1 (January 2007): 140–50. https://doi.org/10.1118/1.2401667.
Tourassi GD, Harrawood B, Singh S, Lo JY, Floyd CE. Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms. Med Phys. 2007 Jan;34(1):140–50.
Tourassi, Georgia D., et al. “Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms.Med Phys, vol. 34, no. 1, Jan. 2007, pp. 140–50. Pubmed, doi:10.1118/1.2401667.
Tourassi GD, Harrawood B, Singh S, Lo JY, Floyd CE. Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms. Med Phys. 2007 Jan;34(1):140–150.

Published In

Med Phys

DOI

ISSN

0094-2405

Publication Date

January 2007

Volume

34

Issue

1

Start / End Page

140 / 150

Location

United States

Related Subject Headings

  • Subtraction Technique
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Radiographic Image Interpretation, Computer-Assisted
  • Radiographic Image Enhancement
  • Pattern Recognition, Automated
  • Nuclear Medicine & Medical Imaging
  • Mammography
  • Information Theory
  • Information Storage and Retrieval