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Summary: Nucleus modelling and segmentation in cell
clusters
Jes´us Angulo
CMM-Centre de Morphologie Math´ematique, Math´ematiques et Syst`emes, MINES
Paristech; 35, rue Saint Honor´e - 77305 Fontainebleau cedex, FRANCE
jesus.angulo@ensmp.fr
Summary. This paper deals with individual nucleus modelling and segmentation,
from fluorescence labelled images, of cell populations growing in complex clusters.
The proposed approach is based on models and operators from mathematical mor-
phology. Cells are individually marked by the ultimate opening and then are seg-
mented by the watershed transformation. A cell counting algorithm based on classi-
cal results of Boolean model theory is heuristically used to detect errors in segment-
ing clustered nuclei.
1 Introduction
High content screening (HCS) refers to technological platforms for parallel
cells growing in multi-well plates (or in other supports as cell on chip) and fluo-
rescent labelling of proteins of interest (immuno-fluorescence with antibodies,
GFP-tagged proteins), together with image capture by automated microscopy
and subsequent cell image analysis [5]. HCS is of interest for the discovery of
new cellular biology mechanisms (i.e., using siRNA), new pharmaceuticals
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