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The NuCLS dataset contains over 220.000 annotations of cell nuclei in breastcancers. We show how to use these data to create a multi-rater model with theMIScnn Framework to automate the analysis of cell nuclei. For the modelcreation, we use the widespread U-Net approach embedded in a pipeline. Thispipeline provides besides the high performance convolution neural network,several preprocessor techniques and a extended data exploration. The finalmodel is tested in the evaluation phase using a wide variety of metrics with asubsequent visualization. Finally, the results are compared and interpretedwith the results of the NuCLS study. As an outlook, indications are given whichare important for the future development of models in the context of cellnuclei.

Nucleus Segmentation and Analysis in Breast Cancer with the MIScnn Framework