Paper
15 May 2003 Content-based image retrieval as a computer aid for the detection of mammographic masses
Author Affiliations +
Abstract
The purpose of the study was to develop and evaluate a content-based image retrieval (CBIR) approach as a computer aid for the detection of masses in screening mammograms. The study was based on the Digital Database for Screening Mammography (DDSM). Initially, a knowledge database of 1,009 mammographic regions was created. They were all 512x512 pixel ROIs with known pathology. Specifically, there were 340 ROIs depicting a biopsy-proven malignant mass, 341 ROIs with a benign mass, and the remaining 328 ROIs were normal. Subsequently, the CBIR algorithm was implemented using mutual information (MI) as the similarity metric for image retrieval. The CBIR algorithm formed the basis of a knowledge-based CAD system. The system operated as follows. Given a databank of mammographic regions with known pathology, a query suspicious mammographic region was evaluated. Based on their information content, all similar cases in the databank were retrieved. The matches were rank-ordered and a decision index was calculated using the query's best matches. Based on a leave-one out sampling scheme, the CBIR-CAD system achieved an ROC area index Az= 0.87±0.01 and a partial ROC area index 0.90Az = 0.45±0.03 for the detection of masses in screening mammograms.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Georgia D. Tourassi, Rene Vargas-Voracek, and Carey E. Floyd Jr. "Content-based image retrieval as a computer aid for the detection of mammographic masses", Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); https://doi.org/10.1117/12.481105
Lens.org Logo
CITATIONS
Cited by 9 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image retrieval

Mammography

Databases

Image segmentation

Content based image retrieval

Computer aided diagnosis and therapy

Digital imaging

Back to Top