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• W4224240878 abstract "Light-sheet fluorescence microscopy (LSFM) is a high-speed, high-resolution and minimally phototoxic technique for 3D imaging of in vivo and in vitro specimens. LSFM exhibits optical sectioning and when combined with tissue clearing techniques, it facilitates imaging of centimeter scale specimens with micrometer resolution. Although LSFM is ubiquitous, it still faces two main challenges that effect image quality especially when imaging large volumes with high-resolution. First, the light-sheet illumination plane and detection lens focal plane need to be coplanar, however sample-induced aberrations can violate this requirement and degrade image quality. Second, introduction of sample-induced optical aberrations in the detection path. These challenges intensify when imaging whole organisms or structurally complex specimens like cochleae and bones that exhibit many transitions from soft to hard tissue or when imaging deep (> 2 mm). To resolve these challenges, various illumination and aberration correction methods have been developed, yet no adaptive correction in both the illumination and the detection path have been applied to improve LSFM imaging. Here, we bridge this gap, by implementing the two correction techniques on a custom built adaptive LSFM. The illumination beam angular properties are controlled by two galvanometer scanners, while a deformable mirror is positioned in the detection path to correct for aberrations. By imaging whole porcine cochlea, we compare and contrast these correction methods and their influence on the image quality. This knowledge will greatly contribute to the field of adaptive LSFM, and imaging of large volumes of tissue cleared specimens." @default.
• W4224240878 created "2022-04-26" @default.
• W4224240878 creator A5032447166 @default.
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• W4224240878 date "2022-04-22" @default.
• W4224240878 modified "2023-10-16" @default.
• W4224240878 title "Quantitative analysis of illumination and detection corrections in adaptive light sheet fluorescence microscopy" @default.
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• W4224240878 doi "https://doi.org/10.1364/boe.454561" @default.
• W4224240878 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35774332" @default.
• W4224240878 hasPublicationYear "2022" @default.
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