Xenopus tissue data for testing segmentation models

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"