Optical characterization of the microstructure of multi-layered biological tissues

This project builds on the hypothesis that combining high-resolution 3D images of tissue microstructure with flexible and accurate light propagation models will allow to perform in-silico design of dedicated optical sensors for non-destructive characterization of the microstructure and composition of biological tissues. Two tomographic techniques will be used in order to visualize the 3D microstructure of biological samples. Mainly the sample porosity will be looked at as a key parameter, both influencing sample microstructure and optical behavior. As a first step, sugar pectin gels with a controllable porosity will be visualized. This will give an idea of the resolution and the differences between both techniques. Secondly, the obtained microstructural information will be translated into a tissue mesh used as an input for light propagation simulations. To model the light propagation in biological tissues, Monte Carlo simulations will be used. A tissue can be segmented into assumed-to-be homogeneous layers, leading to a more realistic approach of for example fruit samples consisting of several layers, e.g. peel and cortex layer(s).

A final step will be to validate the built models. This will be achieved by measuring model systems, with known optical and microstructural properties. Multi-layered model systems will be created in order to validate the simulated light propagation. This will be achieved by measuring samples with a spatially resolved spectroscopy setup and comparing the measured and predicted diffuse reflectance.