Data for: Image processing tools for petabyte-scale light sheet microscopy data (Part 2/2)
Data files
Jul 12, 2024 version files 255.33 GB
-
20220131_Korra_ExM_VNC_2ndtry.zip
255.33 GB
-
README.md
4.12 KB
Jul 12, 2024 version files 255.33 GB
-
20220131_Korra_ExM_VNC_2ndtry.zip
255.33 GB
-
README.md
4.37 KB
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.
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. (bioRxiv, 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. (bioRxiv, 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_00msecAbs_000x_00y_00z_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_00msecAbs: time stamps in milliseconds ( is a number)
- 000x: x tile position
- 00y: y tile position ( is a number)
- 00z: 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) to generate the figures in the paper.
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).