Appears in collection : Statistical Modeling for Shapes and Imaging

The marked point process framework has been successfully developed in the field of image analysis to detect a configuration of predefined objects. In this talk I will show how it can be particularly applied to biological imagery. We present a simple model that shows how some of the challenges specific to biological data are well addressed by the methodology. I will describe an extension to this first model to address other challenges due, for example, to the shape variability in biological material. The results illustrate the MPP framework using the 'simcep' algorithm for simulating populations of cells.