A CAD system based on complex networks theory to characterize mass in mammograms

Carolina Y. V. Watanabe; Jonathan S. Ramos; Agma J. M. Traina; Caetano Traina Jr.

doi:10.1117/12.911609

23 February 2012 A CAD system based on complex networks theory to characterize mass in mammograms

Carolina Y. V. Watanabe, Jonathan S. Ramos, Agma J. M. Traina, Caetano Traina Jr.

Proceedings Volume 8315, Medical Imaging 2012: Computer-Aided Diagnosis; 831522 (2012) https://doi.org/10.1117/12.911609
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

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.

Citation Download Citation

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

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available