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Proceedings Paper

A CAD system based on complex networks theory to characterize mass in mammograms
Author(s): Carolina Y. V. Watanabe; Jonathan S. Ramos; Agma J. M. Traina; Caetano Traina Jr.
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Paper Abstract

This paper presents a Computer-Aided Diagnosis (CAD) system for mammograms, which is based on complex networks to shape boundary characterization of mass in mammograms, suggesting a "second opinion" to the health specialist. A region of interest (the mass) is automatically segmented using an improved algorithm based on EM/MPM and the shape is modeled into a scale-free complex network. Topological measurements of the resulting network are used to compose the shape descriptors. The experiments comparing the complex network approach with other traditional descriptors, in detecting breast cancer in mammograms, show that the proposed approach accomplish the best values of accuracy. Hence, the results indicate that complex networks are wellsuited to characterize mammograms.

Paper Details

Date Published: 23 February 2012
PDF: 12 pages
Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 831522 (23 February 2012); doi: 10.1117/12.911609
Show Author Affiliations
Carolina Y. V. Watanabe, Federal Univ. of Rondônia (Brazil)
Univ. of São Paulo (Brazil)
Jonathan S. Ramos, Federal Univ. of Rondônia (Brazil)
Agma J. M. Traina, Univ. of São Paulo (Brazil)
Caetano Traina Jr., Univ. of São Paulo (Brazil)

Published in SPIE Proceedings Vol. 8315:
Medical Imaging 2012: Computer-Aided Diagnosis
Bram van Ginneken; Carol L. Novak, Editor(s)

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