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Data for: Image processing tools for petabyte-scale light sheet microscopy data (Part 2/2)

Ruan, Xiongtao1; Mueller, Matthew1; Liu, Gaoxiang1; Görlitz, Frederik1; Fu, Tian-Ming2; Milkie, Daniel E.2; Lillvis, Joshua L.2; Kuhn, Alexander3; Chong, Johnny Gan1; Hong, Jason Li1; Herr, Chu Yi Aaron1; Hercule, Wilmene1; Nienhaus, Marc3; Killilea, Alison N.1; Betzig, Eric1; Upadhyayula, Srigokul1

Research facility: University of California, Berkeley
Published Jul 12, 2024 on Dryad. https://doi.org/10.5061/dryad.jq2bvq8jd

Data files

Jul 12, 2024 version files 255.33 GB
Jul 12, 2024 version files 255.33 GB

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Abstract

Light sheet microscopy is a powerful technique for high-speed 3D imaging of subcellular dynamics and large biological specimens. However, it often generates datasets ranging from hundreds of gigabytes to petabytes in size for a single experiment. Conventional computational tools process such images far slower than the time to acquire them and often fail outright due to memory limitations. To address these challenges, we present PetaKit5D, a scalable software solution for efficient petabyte-scale light sheet image processing. This software incorporates a suite of commonly used processing tools that are memory and performance-optimized. Notable advancements include rapid image readers and writers, fast and memory-efficient geometric transformations, high-performance Richardson-Lucy deconvolution, and scalable Zarr-based stitching. These features outperform state-of-the-art methods by over one order of magnitude, enabling the processing of petabyte-scale image data at the full teravoxel rates of modern imaging cameras. The software opens new avenues for biological discoveries through large-scale imaging experiments.