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          Institute: MPI für molekulare Zellbiologie und Genetik     Collection: MPI-CBG Publications 2016 (archival)     Display Documents



ID: 732510.0, MPI für molekulare Zellbiologie und Genetik / MPI-CBG Publications 2016 (archival)
Adaptive light-sheet microscopy for long-term, high-resolution imaging in living organisms.
Authors:Royer, Loic; Lemon, William; Chhetri, Raghav K; Wan, Yinan; Coleman, Michael; Myers, Eugene W; Keller, Patrick
Date of Publication (YYYY-MM-DD):2016
Title of Journal:Nature biotechnology
Volume:34
Issue / Number:12
Start Page:1267
End Page:1278
Copyright:not available
Audience:Experts Only
Intended Educational Use:No
Abstract / Description:Optimal image quality in light-sheet microscopy requires a perfect overlap between the illuminating light sheet and the focal plane of the detection objective. However, mismatches between the light-sheet and detection planes are common owing to the spatiotemporally varying optical properties of living specimens. Here we present the AutoPilot framework, an automated method for spatiotemporally adaptive imaging that integrates (i) a multi-view light-sheet microscope capable of digitally translating and rotating light-sheet and detection planes in three dimensions and (ii) a computational method that continuously optimizes spatial resolution across the specimen volume in real time. We demonstrate long-term adaptive imaging of entire developing zebrafish (Danio rerio) and Drosophila melanogaster embryos and perform adaptive whole-brain functional imaging in larval zebrafish. Our method improves spatial resolution and signal strength two to five-fold, recovers cellular and sub-cellular structures in many regions that are not resolved by non-adaptive imaging, adapts to spatiotemporal dynamics of genetically encoded fluorescent markers and robustly optimizes imaging performance during large-scale morphogenetic changes in living organisms.
External Publication Status:published
Document Type:Article
Communicated by:Thüm
Affiliations:MPI für molekulare Zellbiologie und Genetik
Identifiers:LOCALID:6701
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