Title: Statistical analysis of Raman spectroscopic images, with applications to clinical assessment of bone structure parameters
Co-Advisors: Associate Professor Liza Levina, Associate Professor Kerby Shedden
Committee Member: Professor Naisyin Wang
Abstract: Raman spectroscopy is a technique that can be used to study the chemical composition of a given specimen by the illumination of given samples with a laser beam, collection of the resulting scattered light, and analysis of the subsequent spectral data. The analysis of Raman-spectroscopic data can be challenging due to the high-dimensional nature of spectra and the prevalence of a large amount of noise due to the relative weakness of Raman scattering. Existing methods that aim to address these issues sometimes ignore the spatial structure and/or the functional nature of the data. We propose a method that estimates the salient features of a spectral peak: location, height, and width. Due to its noninvasive nature and ability to capture information specific to chemical bonds and molecular fingerprints, Raman spectroscopy has a wide range of potential applications. For instance, it could be used to predict changes in human bone composition, which may result from the onset of osteoporosis and bone graft healing.