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Automated aberration correction for STED microscopy

dc.contributor.advisorEgner, Alexander Prof. Dr.
dc.contributor.authorGhosh, Debadrita
dc.titleAutomated aberration correction for STED microscopyde
dc.contributor.refereeEgner, Alexander Prof. Dr.
dc.subject.gokPhysik (PPN621336750)de
dc.description.abstractengStimulated emission depletion (STED) microscopy is a powerful super resolution fluorescence microscopy technique that surpasses the diffraction limit. However, the performance of a STED microscope can be adversely influenced by aberrations. In thick biological specimens, aberrations are primarily induced by wavefront distortion caused by variations in the refractive index within the specimen. These aberrations have a substantial impact on the quality of the acquired images and impose limitations on the achievable resolution. This problem can be resolved by using adaptive optics (AO) in a feedback controlled manner such that the wavefront distortions are appropriately compensated, and the image quality is restored. In most cases, the feedback loop in aberration correction techniques relies on using a combination of certain image features as a metric. This approach often requires multiple acquisitions of the same field of view (FOV) to assess and optimize the metric. However, this process is inherently slow and can be prone to unwanted photo bleaching effects. In this thesis, a novel AO based correction scheme is developed, utilizing a newly patented metric. This metric distinguishes itself from traditional methods by not relying on image features but instead capitalizes on the relationship between the fluorescence lifetime and the intensity of the depletion beam employed in STED microscopy. By directly extracting this property from the fluorescence photon stream and utilizing it as a metric, we successfully demonstrate automated and continuous aberration correction for STED imaging and additionally explore its application to confocal imaging. We show that the photon stream-based metric enables swift aberration correction in parallel with image acquisition also in biological samples. This advance significantly speeds up aberration-corrected imaging and makes it accessible to users without technical
dc.contributor.coRefereeEnderlein, Jörg Prof. Dr.
dc.subject.engAdaptive opticsde
dc.affiliation.instituteFakultät für Physikde
dc.notes.confirmationsentConfirmation sent 2023-09-26T19:45:01de

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