Widefield light sheet microscopy using an Airy beam combined with deep-learning super-resolution

Stella Corsetti (Lead / Corresponding author), Philip Wijesinghe, Persephone B. Poulton, Shuzo Sakata, Kushi Vyas, Simon Herrington, Jonathan Nylk, Federico M. Gasparoli, Kishan Dholakia (Lead / Corresponding author)

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)
82 Downloads (Pure)

Abstract

Imaging across length scales and in depth has been an important pursuit of widefield optical imaging. This promises to reveal fine cellular detail within a widefield snapshot of a tissue sample. Current advances often sacrifice resolution through selective sub-sampling to provide a wide field of view in a reasonable time scale. We demonstrate a new avenue for recovering high-resolution images from sub-sampled data in light sheet microscopy using deep-learning super-resolution. We combine this with the use of a widefield Airy beam to achieve high-resolution imaging over extended fields of view and depths. We characterise our method on fluorescent beads as test targets. We then demonstrate improvements in imaging amyloid plaques in a cleared brain from a mouse model of Alzheimer’s disease, and in excised healthy and cancerous colon and breast tissues. This development can be widely applied in all forms of light sheet microscopy to provide a two-fold increase in the dynamic range of the imaged length scale. It has the potential to provide further insight into neuroscience, developmental biology, and histopathology.
Original languageEnglish
Pages (from-to)1068-1083
Number of pages16
JournalOSA Continuum
Volume3
Issue number4
Early online date14 Apr 2020
DOIs
Publication statusPublished - 15 Apr 2020

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