A unified framework for automated 3-d segmentation of surface-stained living cells and a comprehensive segmentation evaluation.

This work presents a unified framework for whole cell segmentation of surface stained living cells from 3-D data sets of fluorescent images. Every step of the process is described, image acquisition, prefiltering, ridge enhancement, cell segmentation, and a segmentation evaluation. The segmentation results from two different automated approaches for segmentation are compared to manual segmentation of the same data using a rigorous evaluation scheme. This revealed that combination of the respective cell types with the most suitable microscopy method resulted in high success rates up to 97%. The described approach permits to automatically perform a statistical analysis of various parameters from living cells.