Bachelor & Master Thesis Projects

We welcome driven students with a background in physics, nanobiology, microscopy, or data science who want to work at the interface of computational imaging and biomedical research - either on the experimental side (microscopy, hardware, tissue preparation) or on the computational side (image processing and signal analysis).

If you are interested, please contact Miriam Menzel for possible projects.

Computational Scattered Light Imaging (ComSLI) resolves nerve fiber pathways and their crossings with micrometer resolution. While other scattering techniques raster-scan the tissue with a light beam and measure the distribution of scattered light behind the sample, ComSLI uses a reverse setup: The whole tissue section is illuminated from many different angles and the normally transmitted light is measured, thus enabling much higher resolutions and requiring only standard optical components (LED light source and camera). This makes ComSLI a highly promising imaging technique, enabling to disentangle complex fiber structures - not only in brain tissue, but also in other biological tissues with comparable fiber structures (e.g. muscle or collagen).

Master Thesis Projects (MEP) - Examples

Start: anytime from June 2024

Analyzing fiber sizes using different wavelengths

It is expected that the scattering of light depends on the feature size relative to the wavelength. In this project, we will systematically compare scattering signals obtained from measurements with different wavelengths on various tissue sections, to better understand how they are related to the underlying fiber structures, and how these measurements can be used to estimate the fiber sizes.

Exploiting tissue composition with polarized light scattering

In brain tissue sections, an interesting effect has been observed: Some regions let more light through when the light is polarized parallel to the nerve fibers. Other regions let more light through when the light is polarized perpendicular to the nerve fibers. In this project, we will study to what degree this effect is caused by scattering and how it can be used to distinguish different tissue regions. Apart from brain tissue, we will measure biological tissues with other types of fibers (muscle, collagen) to see if they show similar effects.

Combining fluorescence and scattered light imaging

Computational Scattered Light Imaging allows to distinguish intricately entangled fibers (nerves, collagen, etc.) and their intersections at micrometer scale. Whole-slide fluorescence microscopy enables high-throughput scanning and digitization of an entire microscope slide. It has significant applications in pathology, allowing for rapid screening and analysis of tissue samples. In this project, we will develop an imaging system that combines fluorescence and scattered light imaging.

Confidence map for scattered light imaging measurements

Currently, the measurement results are mostly compared qualitatively, making it difficult to optimize measurements and judge differences between samples. In this project, we will develop a quality measure to better quantify the measured scattering signals and develop a confidence map to indicate the reliability of computed fiber orientations, taking regional information into account.