ZeroCostDL4Mic - Label-free prediction (fnet) example training and test dataset
Creators
- 1. Institute of Physical and Theoretical Chemistry, Goethe-University Frankfurt, Frankfurt, Germany
Description
Name: ZeroCostDL4Mic - Label-free prediction (fnet) example training and test dataset
(see our Wiki for details)
Data type: 3D paired microscopy images (fluorescence and transmitted light)
Microscopy data type: Confocal microscopy data (TOM20 labeled with Alexa Fluor 594)
Microscope: Leica SP8, HC PL APO 63x 1.40 NA oil objective
Cell type: HeLa (fixed using an organelle-preserving protocol)
File format: .tif (8-bit)
Image size: 512 x 512 x 32 (Pixel size: x and y: 90 nm pixel size, z: 150 nm)
Author(s): Christoph Spahn
Contact email: c.spahn@chemie.uni-frankfurt.de, heilemann@chemie.uni-frankfurt.de
Affiliation: Institute of Physical and Theoretical Chemistry, Goethe-University Frankfurt, Frankfurt, Germany
Associated publications: Unpublished
Funding body(ies): M.H. and C.S.: German Science Foundation (grant nr. SFB1177). C.S.: European Molecular Biology Organization (short term fellowship 8589)
Notes
Files
Label-free prediction (fnet) v2.zip
Files
(666.1 MB)
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Additional details
Related works
- Is part of
- Preprint: 10.1101/2020.03.20.000133 (DOI)