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Signal Improved ultra-Fast Light-sheet Microscope (SIFT) for large tissue imaging

2023 4 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 35 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Md Nasful Huda Prince, Benjamin Garcia, C. Henn, Yating Yi, Etsuo A. Susaki, Yuki Watakabe, Tomomi Nemoto, Keith A. Lidke, Hu Zhao, Irene Salinas Remiro, Sheng Liu, Tonmoy Chakraborty

Summary

Researchers developed Signal Improved ultra-Fast Light-sheet Microscope (SIFT) using two fixed distant light-sheet foci to enable axially swept light-sheet microscopy (ASLM) at 40 frames per second across a full field of view, achieving four-fold speed improvement over current state-of-the-art for large cleared tissue imaging.

Abstract Light-sheet fluorescence microscopy (LSFM) in conjunction with tissue clearing techniques enables morphological investigation of large tissues faster and with excellent optical sectioning. Recently, cleared tissue axially swept light-sheet microscope (ctASLM) demonstrated three-dimensional isotropic resolution in millimeter-scaled tissues. But ASLM based microscopes suffer from low detection signal and slow imaging speed. Here we report a simple and efficient imaging platform that employs precise control of two fixed distant light-sheet foci to carry out ASLM. This allowed us to carry out full field of view (FOV) imaging at 40 frames per second (fps) which is a four-fold improvement compared to the current state-of-the-art. In addition, in a particular frame rate, our method doubles the signal compared to the current ASLM technique. To augment the overall imaging performance, we also developed a deep learning based tissue information classifier that enables faster determination of tissue boundary. We demonstrated the performance of our imaging platform on various cleared tissue samples and demonstrated its robustness over a wide range of clearing protocols.

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