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23 February 2012 A CAD system based on complex networks theory to characterize mass in mammograms
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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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Carolina Y. V. Watanabe, Jonathan S. Ramos, Agma J. M. Traina, and Caetano Traina Jr. "A CAD system based on complex networks theory to characterize mass in mammograms", Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 831522 (23 February 2012); https://doi.org/10.1117/12.911609
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