Segmentation of HeLa cells in phase-contrast images with and without DAPI stained cell nuclei

Microscopy is an essential tool for the observation of microbial effectors in host cells. Manual evaluation of the acqui- red image data is elaborate and error prone. Thus, in order to increase objectivity and reproducibility of results, an automated evaluation of the experiment is performed. The present study evaluates methods to delineate HeLa cells depicted in phase-contrast (PC) micrographs, with and without the additional use of the DAPI stained cell nuclei. For initial cell detection a variance filter is applied to the PC micrographs. Based on this foreground cells are segmented with an intensity based k-means clustering. In a second step, the foreground areas are refined to match the cell boarders by region growing on the background. These foreground areas are used to study the performance of cell separation methods, namely seeded watershed (SW) and graph cuts (GC). Either the maxima of the distance transform of the foreground regions in the PC images (?dist?) or alternatively regions of the cell nuclei (?nuc?) obtained from the DAPI channel are utilized to initialize the cell separation methods. For the detailed evaluation of segmentation quality the cells were categorized to four classes, namely isolated cells, touching cells, overlapping and overlaying cells. With regards the rating of the obtained performance using the Jaccard overlap measure, an intra-observer variance was determined as the median of performance values of all cells with p=0.79. The performance using seeds of type ?dist? resulted in pSW(dist)=0.59 for watershed transform and pGC(dist)=0.60 for graph cuts. Switching seeds to type ?nuc? performance improved to pSW(nuc)=0.72 for watershed transform and pGC(nuc)=0.69 for graph cuts.