Data for: Characterization, comparison, and optimization of lattice light sheets (Part 1/3)
Liu, Gaoxiang et al. (2023), Data for: Characterization, comparison, and optimization of lattice light sheets (Part 1/3), Dryad, Dataset, https://doi.org/10.6078/D1VT6K
Lattice light sheet microscopy excels at the non-invasive imaging of three-dimensional (3D) dynamic processes at high spatiotemporal resolution within cells and developing embryos. Recently, several papers have called into question the performance of lattice light sheets relative to the Gaussian sheets most common in light sheet microscopy. Here we undertake a comprehensive theoretical and experimental analysis of various forms of light sheet microscopy which both demonstrates and explains why lattice light sheets provide significant improvements in resolution and photobleaching reduction. The analysis provides a procedure to select the correct light sheet for a desired experiment and specifies the processing that maximizes the use of all fluorescence generated within the light sheet excitation envelope for optimal resolution while minimizing image artifacts and photodamage. Development of a new type of “harmonic balanced” lattice light sheet is shown to improve performance at all spatial frequencies within its 3D resolution limits and maintains this performance over lengthened propagation distances allowing for expanded fields of view.
The dataset was collected with homemade lattice light sheet microscope with different light sheets and different parameters. The light sheet name and the parameters are contained within the zip file name for the light sheet.
The dataset has been processed with LLSM5DTools (https://github.com/abcucberkeley/LLSM5DTools/tree/dev).
The files can be opened with any 3D image visualization tools (i.e., Fiji, napari, Imaris and Amira) with support for tiff format.
Howard Hughes Medical Institute
Chan Zuckerberg Initiative, Award: Imaging Scientist program
Alexander von Humboldt-Stiftung, Award: Feodor Lynen Research Fellowship
Chan Zuckerberg Biohub