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Effectiveness of Asymmetry Analysis Technique Based on Statistical Features in Breast Cancer Detection with Modern Thermographic Imaging Systems

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CMBEBIH 2019 (CMBEBIH 2019)

Part of the book series: IFMBE Proceedings ((IFMBE,volume 73))

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Abstract

This paper discusses the diagnostic performance of the modern medical thermal imaging system with the other imaging modalities for breast cancer detection. In this study, the digital infrared thermal imaging system is used for analyzing the thermal images of the 270 breast patients diagnosed by the conventional imaging techniques. The thermographic images of these patients are analyzed and then classified according to the 6 different BI-RADS categories by means of the asymmetry analysis technique based on the commonly used 11 statistical features. Finally, higher sensitivity, specificity values and higher accuracy rates are obtained for the 270 breast patients.

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Acknowledgements

I would like to thank Prof. Dr. Serap Gultekin, who is radiologist in Gazi University Radiology Department, for her helps in screening process of the breast patients and for accessing the clinical results of these patients obtained from conventional imaging modalities.

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Authors and Affiliations

  1. Electrical and Electronics Engineering Department, Engineering Faculty, Gazi University, 06570, Ankara, Turkey

    Irfan Karagoz

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  1. Irfan Karagoz
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Correspondence to Irfan Karagoz .

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Editors and Affiliations

  1. International Burch University, Sarajevo, Bosnia and Herzegovina

    Almir Badnjevic

  2. Faculty of Medicine, University of Banja Luka, Banja Luka, Bosnia and Herzegovina

    Ranko Škrbić

  3. International Burch University, Sarajevo, Bosnia and Herzegovina

    Lejla Gurbeta Pokvić

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Karagoz, I. (2020). Effectiveness of Asymmetry Analysis Technique Based on Statistical Features in Breast Cancer Detection with Modern Thermographic Imaging Systems. In: Badnjevic, A., Škrbić, R., Gurbeta Pokvić, L. (eds) CMBEBIH 2019. CMBEBIH 2019. IFMBE Proceedings, vol 73. Springer, Cham. https://doi.org/10.1007/978-3-030-17971-7_25

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  • DOI: https://doi.org/10.1007/978-3-030-17971-7_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-17970-0

  • Online ISBN: 978-3-030-17971-7

  • eBook Packages: EngineeringEngineering (R0)

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