Mouse brain lightfield-confocal stack dataset

Citation Author(s):
Josue
Page
Computational Imaging and Inverse Problems Group, Technical University of Munich
Federico
Saltarin
Theodor Kocher Institute, University of Bern, Switzerland
Yury
Belyaev
Microscopy Imaging Center, University of Bern, Switzerland
Ruth
Lyck
Theodor Kocher Institute, University of Bern, Switzerland
Tobias
Lasser
Computational Imaging and Inverse Problems Group, Technical University of Munich
Paolo
Favaro
Computer Vision Group, University of Bern, Switzerland
Submitted by:
Josue Page
Last updated:
Tue, 05/17/2022 - 22:18
DOI:
10.21227/eagc-ta82
Data Format:
HDF5
Research Article Link:
Learning to Reconstruct Confocal Microscopy Stacks From Single Light Field Images
Links:
Project Page
License:
Creative Commons Attribution
502 Views
Categories:
Biomedical and Health Sciences
Keywords:
Light field, confocal microscopy, 3D, Deep Learning
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Abstract 

Dataset of fluorescent mice brain vessels Confocal 3D volumes aligned to Light-Field images.

Confocal:

  • Single volume dimension: 1287x1287x64.
  • Number of samples: 362
  • Voxel size: 0.086x0.086x0.9 um.
  • Objective: 40x/1.3 Oil.
  • Stain: tomato lectin (DyLight594 conjugated, DL-1177, Vector Laboratories).

 

LightField:

  • Image dimensions 1287x1287.
  • PixelSize: 3.45 um.
  • Pixels per lenslet: 33x33.
  • Lenslet Pitch: 112 um.
  • MLA2Sensor distance: 2500um.
  • Tube-lens focal length: 165mm.
  • Objective: 40x/0.9 Air.

 

H5 containing:

  • volData: confocal volumes 1287x1287x64 voxels.
  • LFData: LF 4D tensor 33x33x39x39 (Angular coord x, angular coord y, spatial coord x, spatial coord y).
  • gridCoords: image grid positions.
Instructions: 

Rename the file extension from hdf5 to .h5

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