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Pix2pix training dataset for predicting nuclei form brightfield images

<p>Dataset for training pix2pix model to predict nuclei from brightfield images of MDA-MB-231.&nbsp;</p><p>This dataset contains 1600 brightfield and 1600 nuclei images.&nbsp;</p><p>The nuclei were labeled using sir-DNA (Cytoskeleton). Cells were imaged live (37 °C, 5% CO2) using a Nikon Eclipse Ti2-E microscope (Nikon) equipped with an sCMOS Orca Flash4.0 camera (Hamamatsu) and controlled by the NIS-Elements software (Nikon, v 5.11.01). MDA-MB-231 cells were imaged using a 20× Nikon CFI Plan Apo Lambda objective (NA 0.75), either 1 frame per minute for 2 hours or 1 frame every 5 minutes for 17 hours. In these experiments, a camera binning of 2 × 2 was used.&nbsp;</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
20
Reuse readiness
8
Engagement
0

Dataset details

Repository
zenodo
Published
November 5, 2023
License
cc-by-4.0
DOI
10.5281/zenodo.10074470

Scored with release 0.9.0

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