Computational Methods for Analysis of Dynamic Events in Cell Migration

Abstract

Cell migration is a complex biological process that involves changes in shape and organization at the sub-cellular, cellular, and supra-cellular levels. Individual and collective cell migration can be assessed in vitro and in vivo starting from the flagellar driven movement of single sperm cells or bacteria, bacterial gliding and swarming, and amoeboid movement to the orchestrated movement of collective cell migration. One key technology to access migration phenomena is the combination of optical microscopy with image processing algorithms. This approach resolves simple motion estimation (e.g. preferred direction of migrating cells or path characteristics), but can also reveal more complex descriptors (e.g. protrusions or cellular deformations). In order to ensure an accurate quantification, the phenomena under study, their complexity, and the required level of description need to be addressed by an adequate experimental setup and processing pipeline. Here, we review typical workflows for processing starting with image acquisition, restoration (noise and artifact removal, signal enhancement), registration, analysis (object detection, segmentation and characterization) and interpretation (high level understanding). Image processing approaches for quantitative description of cell migration in 2- and 3-dimensional image series, including registration, segmentation, shape and topology description, tracking and motion fields are presented. We discuss advantages, limitations and suitability for different approaches and levels of description.