This dataset is of xenopus tissue imaged with the following settings and it comes with a trained UNET model for performing the segmentation of such tissues. In order to use the segmentation model please install the vollseg-napari plugin from the napari hub and the model will be automatically downloaded for usage. Dataset was acquired by Mari Tolonen and Jakub Sedzinski, (0000-0002-4395-9022,0000-0002-1788-0329) at the university of Copenhagen and the model was trained by Varun Kapoor at Kapoorlabs. A Z projection of 21 Z slices acquired by the ImageJ Z Projection plugin was performed on the original acquired data. ObjectiveSettings ID="Objective:0" Medium="Water" RefractiveIndex="1.333" LensNA="1.2000000000000002" Model="C-Apochromat 40x/1.2 W AutoCorr M27" NominalMagnification="40.0" Physical Size X="0.6918881841365326" Physical Size X Unit="µm" Physical Size Y="0.6918881841365326" Physical Size Y Unit="µm" Physical Size Z="2.0" Physical Size Z Unit="µm" Time interval frames 1-160: 182 sec Time interval frames 161-262: 283 sec SignificantBits="8" Type="uint8"> Channel AcquisitionMode="LaserScanningConfocalMicroscopy" ExcitationWavelength="488.0" ExcitationWavelengthUnit="nm" Fluor="EGFP"

Computational support provided by Jean Zay dynamic access grant: AD011013396 Monetary Support by Grant#: 2021-240715(5022) from Chan Zuckerberg Innitiative and Silicon Valley community foundation.