Contralateral asymmetry for breast cancer detection: A CADx approach

• Autorzy: Celaya-Padilla J. M. , Guzmán-Valdivia C. H. , Galván-Tejada C. E. , Galván-Tejada J. I. , Gamboa-Rosales H. , Garza-Veloz I. , Martinez-Fierro M. L. , Cid-Báez M. A. , Martinez-Torteya A. , Martinez-Ruiz F. J. , Luna-García H. , Moreno-Baez A. , Nandal A.

Identyfikatory

DOI

10.1016/j.bbe.2017.10.005

• Języki publikacji: EN

Abstrakty

EN

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. However, most automated detection algorithms do not take it into account. In this research, 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 subject-wise 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 cancer, aiding in the re-scheduling of the radiologists' image queue, an issue of utmost importance in developing countries.

Słowa kluczowe

EN

breast cancer detection; contralateral asymmetry; CADx approach; machine learning

PL

detekcja raka sutka; asymetria przeciwstronna; uczenie maszynowe

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2018
• Tom: Vol. 38, no. 1
• Strony: 115--125
• Opis fizyczny: Bibliogr. 52 poz., rys., tab., wykr.

Twórcy

autor

Celaya-Padilla J. M.

• CONACyT - Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, 98000 Zacatecas, Mexico

autor

Guzmán-Valdivia C. H.

• CONACyT - Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, 98000 Zacatecas, Mexico

autor

Galván-Tejada C. E.

• Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas, Mexico

autor

Galván-Tejada J. I.

• Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas, Mexico

autor

Gamboa-Rosales H.

• Unidad Académica de Medicina Humana y Ciencias de la Salud, Universidad Autónoma de Zacatecas, Zacatecas, Mexico

autor

Garza-Veloz I.

• Unidad Académica de Medicina Humana y Ciencias de la Salud, Universidad Autónoma de Zacatecas, Zacatecas, Mexico

autor

Martinez-Fierro M. L.

• Unidad Académica de Medicina Humana y Ciencias de la Salud, Universidad Autónoma de Zacatecas, Zacatecas, Mexico

autor

Cid-Báez M. A.

• Unidad Académica de Medicina Humana y Ciencias de la Salud, Universidad Autónoma de Zacatecas, Zacatecas, Mexico

autor

Martinez-Torteya A.

• Universidad de Monterrey, San Pedro Garza García, Nuevo Leon, Mexico

autor

Martinez-Ruiz F. J.

• Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas, Mexico

autor

Luna-García H.

• Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas, Mexico

autor

Moreno-Baez A.

• Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas, Mexico

autor

Nandal A.

• University of Science and Information Technology, Ohrid, Macedonia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).