Matsuda, Seiichi P. T.2018-12-032018-12-032009Weber, Crystal Elaine. "Model-based analysis of tissue reflectance and autofluorescence for improved cancer detection." (2009) Diss., Rice University. <a href="https://hdl.handle.net/1911/103748">https://hdl.handle.net/1911/103748</a>.https://hdl.handle.net/1911/103748Improving early detection of cancer represents the most promising opportunity to reduce the mortality and morbidity of cancer. This thesis presents model-based analysis of tissue reflectance and autofluorescence which is used to improve our understanding of the biological basis of tissue spectra in the uterine cervix and oral cavity. An analytical model to extract biologically and diagnostically relevant parameters from clinical measurements of cervical tissue is developed, validated, and implemented. In addition, Monte Carlo based models are used to investigate the effect of dysplastic progression and benign inflammation on oral cavity spectra. Results show depth-sensitive spectroscopy may be able to improve cancer detection and be used as an adjunct to wide field imaging where inflammation causes decreased specificity.118 ppengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.Biomedical engineeringApplied sciencesAutofluorescenceCancer detectionTissue reflectanceModel-based analysis of tissue reflectance and autofluorescence for improved cancer detectionThesis751537733THESIS CHEM. 2010 WEBER