Department Imaging Physics
Principal investigator Miriam Menzel
E-mail address m.menzel@tudelft.nl
Website http://menzellab.gitlab.io
3D-Nanoprinting for improved fiber reconstruction with scattered light
In collaboration with the Accardo Lab (3mE, TU Delft)
Computational Scattered Light Imaging is a highly promising new imaging technique, which allows to disentangle highly complex nerve fiber networks in the brain. However, it has mostly been used to generate 2D fiber maps, as tissue samples with well-defined 3D fiber orientations are not available. In this project, we will generate 3D-printed tissue phantoms with different fiber geometries (e.g. crossing fibers, inclined fibers, fibers with different diameters) and measure them with our setup. In this way, we want to validate and improve the current reconstruction of fiber structures from measured scattering signals. The project is a joint TU Delft Bioengineering Institute funded project.
Techniques
- Two-photon polymerization
- Scanning electron microscopy
- Scattered light imaging
- Image analysis
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 between different tissue compositions. Apart from brain, we will measure biological tissues with other types of fibers (muscle, collagen) to see if they show similar effects.
Techniques
- Polarization microscopy
- Scattered light imaging
- Tissue histology
- Image analysis
Analyzing nerve fiber size in brain samples using scattered light of different wavelengths
Supervisors: Miriam Menzel, Hamed Abbasi
Computational Scattered Light Imaging (ComSLI) is a promising new imaging technique that resolves densely interwoven nerve fibers and their crossings with micrometer resolution, by exploiting scattering of visible light. While other techniques require dedicated equipment and time-consuming raster-scanning, ComSLI can be performed with a simple LED light source and camera.
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 ComSLI measurements with different wavelengths on various brain tissue sections, to better understand how they are related to the underlying nerve fiber sizes, and how these measurements can be used to estimate the fiber sizes.
Techniques
- Scattered light imaging measurements
- Automated signal and image analysis (using ImageJ/Python)
Further reading
Menzel, M., et al. (2021). Frontiers in Neuroanatomy, 15, 767223. DOI: 10.3389/fnana.2021.767223.
Confidence map for scattered light imaging measurements of fibrous tissue samples
Currently, measurement results from Computational Scattered Light Imaging (ComSLI) are mostly compared qualitatively because a quality measure is missing. This makes it difficult to optimize measurement parameters or make informed statements about differences between samples. Also, the measured scattering signals are only interpreted by a simple peak-finding algorithm – the strength and clarity of the signals are not taken into account. In this project, we will develop a quality measure to better quantify the results of ComSLI (scattering patterns, line profiles, etc.), and develop a confidence map to indicate how reliable the computed fiber orientations are. We will identify questionable outliers by taking regional information and information from surrounding pixels into account.
Techniques
Signal and image analysis (using ImageJ and Python)
Further reading
Menzel, M., et al. (2021). NeuroImage, 233, 117952. DOI: 10.1016/j.neuroimage.2021.117952.
Development of a combined fluorescence and scattered light imaging system
Computational Scattered Light Imaging (ComSLI) stands as a novel and emerging imaging method capable of distinguishing intricately entangled fibers (nerves, collagen, etc.) and their intersections at a micrometer scale, utilizing the scatter of visible light.
Whole-slide fluorescence microscopy is a specialized form of fluorescence microscopy that allows for the scanning and digitization of an entire microscope slide with high throughput. It has significant applications in pathology, allowing for the rapid screening and analysis of tissue samples.
Techniques
- Optical system development (scattered light imaging, fluorescence imaging)
- Automated image accusation (e.g., using Python)
Further reading
Menzel, M., et al. (2021). NeuroImage, 233, 117952. DOI: 10.1016/j.neuroimage.2021.117952.
Rivenson, Y., et al. (2019). Nature biomedical engineering, 3, 466-477. DOI: 10.1038/s41551-019-0362-y.