title: Segmentation of microscopic cell scenes.
abstract: Different methods for the automated segmentation of microscopic cell scenes are presented with examples. The techniques discussed include edge detection by thresholding, "blob" detection by split-and-merge algorithm, global thresholding using gray-level histograms, hierarchic thresholding using color information, global thresholding using two-dimensional histograms and segmentation by "blob" labeling. Methods are more robust against insignificant changes in the scene and perform more reliably as more a priori knowledge about the scene is incorporated in the segmentation algorithm. The inclusion of both photometric and geometric a priori knowledge can result in a high level of correct segmentations, the cost of which is increased computation time.
authors.forename: C E
authors.initials: CE
authors.lastname: Liedtke
authors.forename: T
authors.initials: T
authors.lastname: Gahm
authors.forename: F
authors.initials: F
authors.lastname: Kappei
authors.forename: B
authors.initials: B
authors.lastname: Aeikens
mesh_terms: D000465:Algorithms; D003584:Cytological Techniques; D006652:Histological Techniques