
Summary This dataset contains multi-channel fluorescence images of MDCK epithelial cells acquired on a Nikon ECLIPSE Ti2 inverted microscope using a Nikon CFI Plan Apo 60x 1.4 NA oil immersion objective. The release includes raw Nikon ND2 files and the processed ground-truth training patches used in our end-to-end learning pipeline. Preview image: For quick visualization. Should not be used for quantitative analysis. For analysis, use the raw ND2 files and the processed patches. Biological sample and labels Sample: MDCK epithelial cellsFluorescence channels and mapping: C0: DAPI C1: F actin C2: Vimentin C3: Lamin A Microscope and acquisition settings System: Nikon Ti2 (ECLIPSE Ti2 inverted microscope)Objective: Nikon CFI Plan Apo 60x 1.4 NA oil immersion, working distance 0.13 mmPixel size: 0.11 µmIllumination: 100 percent LED intensity, pE 4000 (CoolLED) Excitation and emission filters: 385 nm excitation, emission 421 to 445 nm 470 nm excitation, emission 503 to 538 nm 550 nm excitation, emission 582 to 619 nm 635 nm excitation, emission 660 to 701 nm Data contents Raw data: Nikon ND2 files as acquired.Processed data: ground truth patches sized 512 by 512 pixels with 4 channels, prepared for training. How to use Open ND2 files using Nikon NIS Elements, Bio Formats, Fiji, or Python readers that support ND2 via Bio Formats. Training patches can be loaded directly in Python as provided in the zip. Sample preparation See Section 4.4 “Sample preparation” in the associated manuscript for full staining and preparation details. Acknowledgement The authors thank Sanni Erämies regarding her contribution to imaging of MDCK samples, and acknowledge the Biocenter Finland (BF) and Tampere Imaging Facility (TIF) for the service.
Deep Learning, Microscopy, Fluorescence, fluorescence microscopy, MDCK
Deep Learning, Microscopy, Fluorescence, fluorescence microscopy, MDCK
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