ZeroCostDL4Mic - Label-free prediction (fnet) example training and test dataset

<strong>Name</strong>: ZeroCostDL4Mic - Label-free prediction (fnet) example training and test dataset (see our Wiki for details) <strong>Data type</strong>: 3D paired microscopy images (fluorescence and transmitted light) <strong>Microscopy data type</strong>: Confocal microscopy data (TOM20 labeled with Alexa Fluor 594) <strong>Microscope</strong>: Leica SP8, HC PL APO 63x 1.40 NA oil objective <strong>Cell type</strong>: HeLa (fixed using an organelle-preserving protocol) <strong>File format</strong>: .tif (8-bit) <strong>Image size</strong>: 512 x 512 x 32 (Pixel size: x and y: 90 nm pixel size, z: 150 nm) <strong>Author(s)</strong>: Christoph Spahn <strong>Contact email</strong>: [e-mail], [e-mail] <strong>Affiliation</strong>: Institute of Physical and Theoretical Chemistry, Goethe-University Frankfurt, Frankfurt, Germany <strong>Associated publications</strong>: Unpublished <br> <strong>Funding body(ies)</strong>: M.H. and C.S.: German Science Foundation (grant nr. SFB1177). C.S.: European Molecular Biology Organization (short term fellowship 8589)