Colourful Depth : Adaptive Optics and Spectral Unmixing for Single-Molecule Localization Microscopy
Publication date
2022-06-01
Authors
Siemons, Marijn Ewout
Editors
Advisors
Kapitein, L.C.
Kole, M.H.P.
Supervisors
Document Type
Dissertation
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Abstract
Single-Molecule Localization Microscopy is a powerful imaging technique which enables the localization of individual molecules with a precision of a few nanometres. This technique relies on the blinking of individual fluorescent molecules. By recording these blinking events it is possible to reconstruct a single image with more detail compared to standard fluorescence microscopy. This recently developed imaging modality has let to numerous biological discoveries using thin cellular samples, but cannot be easily applied to tissue samples. When imaging inside these samples, the emitted light is disturbed by the sample, which hampers detection and localization. This optical aberration can be corrected by placing a deformable mirror in the collection path of the microscope, a technique called adaptive optics. It is possible to partially correct the aberration by adjusting the deformable mirror. In this thesis I compare different correction methods and quantify the improvement which can be achieved with adaptive optics for localization microscopy.
Another challenge for localization microscopy is the use of differently coloured fluorescent molecules, which are used to stain different structures inside samples. However, the types of fluorescent molecules with suitable blinking properties are similar in colour and are therefore difficult to distinguish. We demonstrate a novel un-mixing method, based on a recent proposed method, which uses photon statistics and is easier to implement on conventional microscopes. The research presented in this thesis enhances the usability of localization microscopy in tissue and improves multi-colour imaging to visualize different structures inside samples.
Keywords
Single-Molecule Localization Microscopy; Adaptive Optics; Multi-colour Imaging; Spectral Demxing; Spectral Unmixing