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Proceedings Paper

Multi-view information fusion for automatic BI-RADS description of mammographic masses
Author(s): Fabián Narvaez; Gloria Díaz; Eduardo Romero M.D.
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Paper Abstract

Most CBIR-based CAD systems (Content Based Image Retrieval systems for Computer Aided Diagnosis) identify lesions that are eventually relevant. These systems base their analysis upon a single independent view. This article presents a CBIR framework which automatically describes mammographic masses with the BI-RADS lexicon, fusing information from the two mammographic views. After an expert selects a Region of Interest (RoI) at the two views, a CBIR strategy searches similar masses in the database by automatically computing the Mahalanobis distance between shape and texture feature vectors of the mammography. The strategy was assessed in a set of 400 cases, for which the suggested descriptions were compared with the ground truth provided by the data base. Two information fusion strategies were evaluated, allowing a retrieval precision rate of 89.6% in the best scheme. Likewise, the best performance obtained for shape, margin and pathology description, using a ROC methodology, was reported as AUC = 0.86, AUC = 0.72 and AUC = 0.85, respectively.

Paper Details

Date Published: 4 March 2011
PDF: 7 pages
Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 79630A (4 March 2011); doi: 10.1117/12.878392
Show Author Affiliations
Fabián Narvaez, National Univ. of Colombia (Colombia)
Gloria Díaz, National Univ. of Colombia (Colombia)
Eduardo Romero M.D., National Univ. of Colombia (Colombia)

Published in SPIE Proceedings Vol. 7963:
Medical Imaging 2011: Computer-Aided Diagnosis
Ronald M. Summers M.D.; Bram van Ginneken, Editor(s)

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