  Extracting single-cell information from microscopy data requires accurate
instance-wise segmentations. Obtaining pixel-wise segmentations from microscopy
imagery remains a challenging task, especially with the added complexity of
microstructured environments. This paper presents a novel dataset for
segmenting yeast cells in microstructures. We offer pixel-wise instance
segmentation labels for both cells and trap microstructures. In total, we
release 493 densely annotated microscopy images. To facilitate a unified
comparison between novel segmentation algorithms, we propose a standardized
evaluation strategy for our dataset. The aim of the dataset and evaluation
strategy is to facilitate the development of new cell segmentation approaches.
The dataset is publicly available at
https://christophreich1996.github.io/yeast_in_microstructures_dataset/ .
