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Breast Cancer Detection Using Infrared Thermal Imaging and a Deep Learning Model
Sebastien Jean Mambou1, Petra Maresova2, Ondrej Krejcar3
1Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Rokitanskeho 62, Hradec Kralove 500 03, Czech Republic. jean.mambou@uhk.cz.
Sensors (Basel, Switzerland)
|August 29, 2018
Summary
Breast cancer prevention is a public health priority. This study compares infrared imaging and computer-aided diagnostics with traditional methods, utilizing deep learning for enhanced breast cancer detection accuracy.
Area of Science:
- Oncology
- Medical Imaging
- Computer Science
Background:
- Breast cancer affects millions globally, necessitating cost-effective and accurate detection methods.
- Mammography, a common diagnostic tool, faces challenges like false positives and potential side effects.
- There is a growing need for advanced breast cancer screening techniques.
Purpose of the Study:
- To conduct a comparative analysis of various breast cancer detection techniques.
- To evaluate the efficacy of infrared digital imaging and Computer-Aided Diagnostic (CAD) systems.
- To explore the application of computer vision and deep learning in breast cancer diagnosis.
Main Methods:
- Literature review focusing on infrared digital imaging principles.
- Development and application of a hemispheric model for CAD in infrared image processing.
- Comparative study using advanced computer vision and deep learning models for breast cancer detection.
Main Results:
- Infrared imaging detects increased thermal activity in cancerous breast tissues.
- Computer-aided diagnostic systems, integrated with infrared imaging, show promise.
- Deep learning models enhance the accuracy of breast cancer detection when applied to medical images.
Conclusions:
- Infrared digital imaging offers a potential alternative or complementary method for breast cancer detection.
- Advanced computational techniques, including deep learning, can significantly improve the diagnostic accuracy of breast cancer screening.
- Further research and validation are warranted for clinical implementation of these novel techniques.
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