Multiple objects detection in biological images using a marked point process framework.
The marked point process framework has been successfully developed in the field of image analysis to detect a configuration of predefined objects. The goal of this paper is to 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. We further describe an extension to this first model to address other challenges due, for example, to the shape variability in biological material. We finally show results that illustrate the MPP framework using the "simcep" algorithm for simulating populations of cells.
Université Côte d'Azur, INRIA CRI-SAM, I3S, iBV, France. Electronic address: xavier.descombes@inria.fr.
Xavier
X
Descombes
D001185:Artificial Intelligence; D003198:Computer Simulation; D005057:Eukaryotic Cells / Q000648:ultrastructure*; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data; D057054:Molecular Imaging / Q000379:methods* / Q000706:statistics & numerical data; D010363:Pattern Recognition, Automated / Q000379:methods* / Q000706:statistics & numerical data
Biological imagery; Marked point process; Object detection