Fractional Entropy Based Active Contour Segmentation of Cell Nuclei in Actin-Tagged Confocal Microscopy Images

Best Student Paper Award; International audience; In the framework of cell structure characterization for predictive oncology, we pro- pose in this paper an unsupervised statistical region based active contour approach in- tegrating an original fractional entropy measure for single channel actin tagged fluo- rescence confocal microscopy image segmentation. Following description of statistical based active contour segmentation and the mathematical definition of the proposed frac- tional entropy descriptor, we demonstrate comparative segmentation results between the proposed approach and standard Shannon's entropy obtained for nuclei segmentation. We show that the unsupervised proposed statistical based approach integrating the frac- tional entropy measure leads to very satisfactory segmentation of the cell nuclei from which shape characterization can be subsequently used for the therapy progress assess- ment.