DOI: 10.5061/dryad.jq2bvq8jd
title: Data for: Image processing tools for petabyte-scale light sheet microscopy data (Part 2/2)

description: 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.
description: The light sheet, 2-photon, and phase images were collected with
 homemade light sheet, 2-photon, and oblique illumination "phase"
 microscopes. The widefield and confocal images were collected with Andor
 BC43 Benchtop Confocal Microscope (Oxford Instruments). 
 The dataset has been processed with PetaKit5D (https://github.com/abcucberkeley/PetaKit5D).
description: # Data for "Image processing tools for petabyte-scale light sheet
 microscopy data (Part 2/2)" --- The image data is organized for the
 figures in the paper "Image processing tools for petabyte-scale light
 sheet microscopy data". Nature Methods
 (2024). [https://doi.org/10.1038/s41592-024-02475-4](https://doi.org/10.1038/s41592-024-02475-4). (bioRxiv, [https://doi.org/10.1101/2023.12.31.573734](https://doi.org/10.1101/2023.12.31.573734)): ## Description of the data and file structure ### Schema of data archive ``` 20220131_Korra_ExM_VNC_2ndtry.zip ├── 20220131_Korra_ExM_VNC_2ndtry │   ├── Data │   │   ├── ImageList_from_encoder.csv │   │   ├── Scan_Iter_0000_000x_00*y_00*z_0000t_JSONsettings.json │   │   ├── Scan_Iter_0000_000x_00*y_00*z_0000t_Settings.txt │   │   ├── Scan_Iter_0000_000x_00*y_00*z_0000t_TargetPositions.csv │   │   ├── Scan_Iter_0000_CamA_ch0_CAM1_stack0000_488nm_0000000msec_00*msecAbs_000x_00*y_00*z_0000t_part0001.tif │   │   ├── Scan_Iter_0000_CamA_ch0_CAM1_stack0000_488nm_0000000msec_00*msecAbs_000x_00*y_00*z_0000t_part0002.tif │   │   ├── Scan_Iter_0000_CamA_ch0_CAM1_stack0000_488nm_0000000msec_00*msecAbs_000x_00*y_00*z_0000t.tif │   │   ├── Scan_Iter_0000_CamB_ch0_CAM1_stack0000_488nm_0000000msec_00*msecAbs_000x_00*y_00*z_0000t_part0001.tif │   │   ├── Scan_Iter_0000_CamB_ch0_CAM1_stack0000_488nm_0000000msec_00*msecAbs_000x_00*y_00*z_0000t_part0002.tif │   │   ├── Scan_Iter_0000_CamB_ch0_CAM1_stack0000_488nm_0000000msec_00*msecAbs_000x_00*y_00*z_0000t.tif │   │   ├── SliceList_Scan_Iter_0000_CamA_ch0_CAM1_stack0000_488nm_0000000msec_00*msecAbs_000x_00*y_00*z_0000t.tifpart0.csv │   │   └── SliceList_Scan_Iter_0000_CamB_ch0_CAM1_stack0000_488nm_0000000msec_00*msecAbs_000x_00*y_00*z_0000t.tifpart0.csv │   └── PSF │   ├── 488nm_p35dp05_JSONsettings.json │   ├── 488nm_p35dp05_Settings.txt │   ├── 488nm_p35dp05_TargetPositions.csv │   ├── 488nm_p35dp05.tif │   ├── 560nm_p35dp05_3p5ms_320FOV_JSONsettings.json │   ├── 560nm_p35dp05_3p5ms_320FOV_Settings.txt │   ├── 560nm_p35dp05_3p5ms_320FOV_TargetPositions.csv │   └── 560nm_p35dp05_3p5ms_320FOV.tif README.md ``` ### File Details This dataset contains the representative datasets for the the paper "Image processing tools for petabyte-scale light sheet microscopy data". Nature Methods (2024). [https://doi.org/10.1038/s41592-024-02475-4](https://doi.org/10.1038/s41592-024-02475-4). (bioRxiv, [https://doi.org/10.1101/2023.12.31.573734](https://doi.org/10.1101/2023.12.31.573734)). #### 20220131\_Korra\_ExM\_VNC\_2ndtry (after decompressing the zip file): Super-Resolution Imaging of the Fly Ventral Nerve Cord (VNC) with 8x Expansion and Lattice Light-Sheet Microscopy Data: folder that contains the image data PSF: folder that contains the PSF images #### 20220131\_Korra\_ExM\_VNC\_2ndtry/Data: ImageList_from_encoder.csv: csv file containing the image list *JSONsettings.json: json file containing meta data *Settings.txt: txt file containing meta data *TargetPositions.csv: csv file containing target positions *_part000*.tif: partial frames after the main image file Scan_Iter_0000_Cam*_ch0_CAM1_stack0000_488nm_0000000msec_00*msecAbs_000x_00*y_00*z_0000t.tif: tiled image data * Scan: image prefix * Iter_0000: absolute timepoint * Cam*_ch0_CAM1: camera and channel (* is the letter A or B) * stack0000: stack number * 488nm: image laser wavelength (may not be exact) * 0000000msec_00*msecAbs: time stamps in milliseconds (* is a number) * 000x: x tile position * 00*y: y tile position (* is a number) * 00*z: z tile position (* is a number) * 0000t: timepoint tile position SliceList*.csv: csv file containing the slice list #### 20220131\_Korra\_ExM\_VNC\_2ndtry/PSF: *JSONsettings.json: json file containing meta data *Settings.txt: txt file containing meta data *TargetPositions.csv: csv file containing target positions *.tif: PSF images ## Code/Software The data was processed with PetaKit5D ([https://github.com/abcucberkeley/PetaKit5D](https://github.com/abcucberkeley/PetaKit5D)) to generate the figures in the paper.