Summary
Optical approaches have been studied for the detection and diagnosis of epithelial cancer. Due to the biochemical and structural changes that occur in cancerous cells, malignant, benign, and normal tissues have different spectral properties. Artificial intelligence (AI) methods are being explored to detect and diagnose cancer based on optical imaging and spectra. AI is also used to optimize the design of optical spectroscopy and imaging instrumentation. In this chapter, we review the literature on AI applied to optical spectroscopy for cancer detection and diagnosis and present a detailed case study of research on oral cancer diagnosis using polarized light spectra.
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© 2008 Springer-Verlag Berlin Heidelberg
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Kan, CW., Nieman, L.T., Sokolov, K., Markey, M.K. (2008). AI in Clinical Decision Support: Applications in Optical Spectroscopy for Cancer Detection and Diagnosis. In: Sordo, M., Vaidya, S., Jain, L.C. (eds) Advanced Computational Intelligence Paradigms in Healthcare - 3. Studies in Computational Intelligence, vol 107. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77662-8_2
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DOI: https://doi.org/10.1007/978-3-540-77662-8_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77661-1
Online ISBN: 978-3-540-77662-8
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