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Raman spectroscopy for human cancer tissue diagnosis: A pattern recognition approach
Department of Electrical and Computer Engineering, Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, USA
Department of Electrical and Computer Engineering and Integrated Nanosystems Development Institute (INDI), Indiana University- Purdue University Indianapolis IUPUI, Indianapolis, USA
Department of Electrical and Computer Engineering and Integrated Nanosystems Development Institute (INDI), Indiana University- Purdue University Indianapolis IUPUI, Indianapolis, USA
Department of Electrical and Computer Engineering and Integrated Nanosystems Development Institute (INDI), Indiana University- Purdue University Indianapolis IUPUI, Indianapolis, USA
Department of Electrical and Computer Engineering and Integrated Nanosystems Development Institute (INDI), Indiana University- Purdue University Indianapolis IUPUI, Indianapolis, USA
- 1 Department of Electrical and Computer Engineering, Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, USA
- 2 Department of Electrical and Computer Engineering and Integrated Nanosystems Development Institute (INDI), Indiana University- Purdue University Indianapolis IUPUI, Indianapolis, USA
- 3 Department of Electrical and Computer Engineering and Integrated Nanosystems Development Institute (INDI), Indiana University- Purdue University Indianapolis IUPUI, Indianapolis, USA
- 4 Department of Electrical and Computer Engineering and Integrated Nanosystems Development Institute (INDI), Indiana University- Purdue University Indianapolis IUPUI, Indianapolis, USA
- 5 Department of Electrical and Computer Engineering and Integrated Nanosystems Development Institute (INDI), Indiana University- Purdue University Indianapolis IUPUI, Indianapolis, USA
Journal of Biomedical Science and Engineering·Volume 05 (2012)·Pages 892–900·Published 31 December 2012·DOI10.4236/jbise.2012.512A113
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Abstract
In this work, optical scattering using Raman spectroscopy has been analyzed for various cancer tissues. The Raman shifts obtained at the Indiana University Bloomington (IUB) and Indiana University-Purdue University Indianapolis (IUPUI) laboratories have been processed for diagnosing various types of cancer tissues. The objective of this research is to distinguish between cancerous and non-cancerous tissues. Small size tissue samples have been processed, seeking the minimum size tissue that can be diagnosed via Raman spectroscopy. The tests have been conducted on nearly 20 human tissues. A Matlab program has been written following Parzen-Window classifier to recognize the Raman shift pattern for various types of cancer tissues, including breast cancer, kidney, and Gyn-Uterus. A software visual model has been used for data processing. Unique signals for breast and kidney tumors have been obtained. The approach followed in this paper shows promise for early cancer detection in humans.
KeywordsCancerTissuesRaman SpectroscopyPattern Recognition
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