28 September 2016 Asymmetry features for classification of thermograms in breast cancer detection
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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.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert M. Nowak, Robert M. Nowak, Rafał Okuniewski, Rafał Okuniewski, Witold Oleszkiewicz, Witold Oleszkiewicz, Paweł Cichosz, Paweł Cichosz, Dariusz Jagodziński, Dariusz Jagodziński, Mateusz Matysiewicz, Mateusz Matysiewicz, Łukasz Neumann, 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); doi: 10.1117/12.2249066; https://doi.org/10.1117/12.2249066
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