Contralateral asymmetry for breast cancer detection: A CADx approach

Jose M. Celaya-Padilla, Cesar H. Guzmán-Valdivia, Carlos E. Galván-Tejada, Jorge I. Galván-Tejada, Hamurabi Gamboa-Rosales, Idalia Garza-Veloz, Margarita L. Martinez-Fierro, Miguel A. Cid-Báez, Antonio Martinez-Torteya, Francisco J. Martinez-Ruiz, Huizilopoztli Luna-García, Arturo Moreno-Baez, Amita Nandal

Research output: Contribution to journalArticle

3 Citations (Scopus)

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. 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.

Original languageEnglish
Pages (from-to)115-125
Number of pages11
JournalBiocybernetics and Biomedical Engineering
Volume38
Issue number1
DOIs
Publication statusPublished - 1 Jan 2018

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Screening
Computer aided diagnosis
Mammography
Electric fuses
Developing countries
Scheduling

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

Cite this

Celaya-Padilla, J. M., Guzmán-Valdivia, C. H., Galván-Tejada, C. E., Galván-Tejada, J. I., Gamboa-Rosales, H., Garza-Veloz, I., ... Nandal, A. (2018). Contralateral asymmetry for breast cancer detection: A CADx approach. Biocybernetics and Biomedical Engineering, 38(1), 115-125. https://doi.org/10.1016/j.bbe.2017.10.005
Celaya-Padilla, Jose M. ; Guzmán-Valdivia, Cesar H. ; Galván-Tejada, Carlos E. ; Galván-Tejada, Jorge I. ; Gamboa-Rosales, Hamurabi ; Garza-Veloz, Idalia ; Martinez-Fierro, Margarita L. ; Cid-Báez, Miguel A. ; Martinez-Torteya, Antonio ; Martinez-Ruiz, Francisco J. ; Luna-García, Huizilopoztli ; Moreno-Baez, Arturo ; Nandal, Amita. / Contralateral asymmetry for breast cancer detection: A CADx approach. In: Biocybernetics and Biomedical Engineering. 2018 ; Vol. 38, No. 1. pp. 115-125.
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Celaya-Padilla, JM, Guzmán-Valdivia, CH, Galván-Tejada, CE, Galván-Tejada, JI, Gamboa-Rosales, H, Garza-Veloz, I, Martinez-Fierro, ML, Cid-Báez, MA, Martinez-Torteya, A, Martinez-Ruiz, FJ, Luna-García, H, Moreno-Baez, A & Nandal, A 2018, 'Contralateral asymmetry for breast cancer detection: A CADx approach', Biocybernetics and Biomedical Engineering, vol. 38, no. 1, pp. 115-125. https://doi.org/10.1016/j.bbe.2017.10.005

Contralateral asymmetry for breast cancer detection: A CADx approach. / Celaya-Padilla, Jose M.; Guzmán-Valdivia, Cesar H.; Galván-Tejada, Carlos E.; Galván-Tejada, Jorge I.; Gamboa-Rosales, Hamurabi; Garza-Veloz, Idalia; Martinez-Fierro, Margarita L.; Cid-Báez, Miguel A.; Martinez-Torteya, Antonio; Martinez-Ruiz, Francisco J.; Luna-García, Huizilopoztli; Moreno-Baez, Arturo; Nandal, Amita.

In: Biocybernetics and Biomedical Engineering, Vol. 38, No. 1, 01.01.2018, p. 115-125.

Research output: Contribution to journalArticle

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AU - Celaya-Padilla, Jose M.

AU - Guzmán-Valdivia, Cesar H.

AU - Galván-Tejada, Carlos E.

AU - Galván-Tejada, Jorge I.

AU - Gamboa-Rosales, Hamurabi

AU - Garza-Veloz, Idalia

AU - Martinez-Fierro, Margarita L.

AU - Cid-Báez, Miguel A.

AU - Martinez-Torteya, Antonio

AU - Martinez-Ruiz, Francisco J.

AU - Luna-García, Huizilopoztli

AU - Moreno-Baez, Arturo

AU - Nandal, Amita

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N2 - 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.

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Celaya-Padilla JM, Guzmán-Valdivia CH, Galván-Tejada CE, Galván-Tejada JI, Gamboa-Rosales H, Garza-Veloz I et al. Contralateral asymmetry for breast cancer detection: A CADx approach. Biocybernetics and Biomedical Engineering. 2018 Jan 1;38(1):115-125. https://doi.org/10.1016/j.bbe.2017.10.005