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Title: Contralateral asymmetry for breast cancer detection : A CADx approach
Authors: Celaya Padilla, José María
Guzmán Valdivia, César Humberto
Galván Tejada, Carlos Eric
Galván Tejada, Jorge Issac
Gamboa Rosales, Hamurabi
Garza Veloz, Idalia
Martínez Fierro, Margarita de la Luz
Cid Báez, Miguel A.
Martínez Torteya, Antonio
Martínez Ruíz, Francisco Javier
Luna García, Huizilopoztli
Moreno Baez, Arturo
Nandal, Amita
Issue Date: 2018
Publisher: Elsevier
Abstract: Early detection is fundamental for the effective treatment of breast cancer and the screening mammography is the most common tool used by the medical community to detect early breast cancer development. Screening mammograms include images of both breasts using two standard views, and the contralateral asymmetry per view is a key feature in detecting breast cancer. we propose a methodology to incorporate said asymmetry information into a computer-aided diagnosis system that can accurately discern between healthy subjects and subjects at risk of having breast cancer. Furthermore, we generate features that measure not only a view-wise asymmetry, but a subject-wise one. Briefly, the methodology co-registers the left and right mammograms, extracts image characteristics, fuses them into subjectwise features, and classifies subjects. In this study, 152 subjects from two independent databases, one with analog- and one with digital mammograms, were used to validate the methodology. Areas under the receiver operating characteristic curve of 0.738 and 0.767, and diagnostic odds ratios of 23.10 and 9.00 were achieved, respectively. In addition, the proposed method has the potential to rank subjects by their probability of having breast
ISSN: 0208-5216
Other Identifiers: info:eu-repo/semantics/publishedVersion
Appears in Collections:*Documentos Académicos*-- Doc. en Ing. y Tec. Aplicada

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