Cellocity: A Python package for analysis of confluent cell layer dynamics

The dataset was generated by translating and imaging, with DIC contrast, a fixed monolayer of murine primary gut epithelium on a high precision linear microscope stage, using a wide selection of magnifications. 10 images were acquired with the stage translated 1 um in either the X, Y or both directions simultaneously between frames. Images were acquired on a Nikon Eclipse Ti-2 microscope equipped with a Photometrics Prime 95B camera (1608x1608, 11 um pixel size). The purpose of the dataset is to act as ground truth and as a test dataset for the Cellocity software framework.