Asymmetry features for classification of thermograms in breast cancer detection

Robert M. Nowak; Rafał Okuniewski; Witold Oleszkiewicz; Paweł Cichosz; Dariusz Jagodziński; Mateusz Matysiewicz; Łukasz Neumann

doi:10.1117/12.2249066

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28 September 2016 Asymmetry features for classification of thermograms in breast cancer detection

Robert M. Nowak, Rafał Okuniewski, Witold Oleszkiewicz, Paweł Cichosz, Dariusz Jagodziński, Mateusz Matysiewicz, Łukasz Neumann

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Proceedings Volume 10031, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2016; 100312W (2016) https://doi.org/10.1117/12.2249066
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2016, 2016, Wilga, Poland

Abstract

The computer system for an automatic interpretation of thermographic pictures created by the Br-aster devices uses image processing and machine learning algorithms. The huge set of attributes analyzed by this software includes the asymmetry measurements between corresponding images, and these features are analyzed in presented paper. The system was tested on real data and achieves accuracy comparable to other popular techniques used for breast tumour detection.

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Robert M. Nowak, Rafał Okuniewski, Witold Oleszkiewicz, Paweł Cichosz, Dariusz Jagodziński, Mateusz Matysiewicz, and Łukasz Neumann "Asymmetry features for classification of thermograms in breast cancer detection", Proc. SPIE 10031, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2016, 100312W (28 September 2016); https://doi.org/10.1117/12.2249066

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