Increasing resolution and light efficiency in fluorescence microscopy

Student thesis: Doctoral ThesisDoctor of Philosophy


Structured illumination microscopy (SIM) can be used to enhance the lateral resolu-tion and the sectioning capability in microscopic imaging. As a wide-field technique it may have advantages over scanning approaches such as stimulated emission depletion (STED) microscopy regarding acquisition time and bleaching. Similar to the genera-tion of moire´ patterns, the structured illumination transposes high spatial frequency information in the sample into low spatial frequency information, which can then be recorded by the microscope and computationally recovered in order to generate high resolution images. However, numerous experimental factors can lead to the generation of artefacts in the final image. Therefore, sophisticated algorithms are needed for the reconstruction of high quality images from raw data. This thesis discusses the experi-mental challenges of structured illumination microscopy and newly developed methods of addressing these in the reconstruction process. The final images show good quality and a resolution improvement of about a factor of two.
Confocal microscopy is another technique used for achieving optical sectioning of biological specimen. By using a pinhole in the detection pathway out-of-focus light is blocked, leading to the desired sectioning effect. Closing the pinhole further also allows an enhancement of the lateral resolution; however this comes at the cost of strongly reduced light efficiency, as less light passes through the pinhole. Adding an interferom-eter with relative image inversion optics between its two arms to the descanned output of a confocal microscope makes it possible to surpass the lateral resolution limit (closed pinhole) of confocal microscopes for large pinholes, significantly increasing the light efficiency of such a microscope. This thesis presents the theoretical description of this method as well as experimental results confirming it.
Date of Award2018
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorRainer Heintzmann (Supervisor) & Klaus Suhling (Supervisor)

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