Depth resolved diffuse reflectance spectroscopy
This dissertation focuses on the development of computational models and algorithms related to diffuse reflectance spectroscopy. Specifically, this work aims to advance diffuse reflectance spectroscopy to a technique that is capable of measuring depth dependent properties in tissue.
First, we introduce the Monte Carlo lookup table (MCLUT) method for extracting optical properties from diffuse reflectance spectra. Next, we extend this method to a two-layer tissue geometry so that it can extract depth dependent properties in tissue. We then develop a computational model that relates photon sampling depth to optical properties and probe geometry. This model can be used to aid in design of application specific diffuse reflectance probes. In order to provide justification for using a two-layer model for extracting tissue properties, we show that the use of a one-layer model can lead to significant errors in the extracted optical properties. Lastly, we use our two-layer MCLUT model and a probe that was designed based on our sampling depth model to extract tissue properties from the skin of 80 subjects at 5 anatomical locations. The results agree with previously published values for skin properties and show that can diffuse reflectance spectroscopy can be used to measured depth dependent properties in tissue.