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

• Published in: Medical physics (Lancaster) Vol. 34; no. 1; p. 140
• Main Authors: Tourassi, Georgia D, Harrawood, Brian, Singh, Swatee, Lo, Joseph Y, Floyd, Carey E
• Format: Journal Article
• Language: English
• Published: United States 01.01.2007
• Subjects: Algorithms; Artificial Intelligence; Breast Neoplasms - diagnostic imaging; Humans; Information Storage and Retrieval - methods; Information Theory; Mammography - methods; Pattern Recognition, Automated - methods; Radiographic Image Enhancement - methods; Radiographic Image Interpretation, Computer-Assisted - methods; Reproducibility of Results; Sensitivity and Specificity; Subtraction Technique
• ISSN: 0094-2405
• DOI: 10.1118/1.2401667

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.