title: Influence of the noise model on level set active contour segmentation.
abstract: We analyze level set implementation of region snakes based on the maximum likelihood method for different noise models that belong to the exponential family. We show that this approach can improve segmentation results in noisy images and we demonstrate that the regularization term can be efficiently determined using an information theory-based approach, i.e., the minimum description length principle. The criterion to be optimized has no free parameter to be tuned by the user and the obtained segmentation technique is adapted to nonsimply connected objects.
authors.affiliation: Physics and Image Processing Group, Institut Fresnel, Dom. Univ. St. Jerome, Marseille Cedex 20, France. pascal.martin@fresnel.fr
authors.forename: Pascal
authors.initials: P
authors.lastname: Martin
authors.forename: Philippe
authors.initials: P
authors.lastname: Réfrégier
authors.forename: François
authors.initials: F
authors.lastname: Goudail
authors.forename: Frédéric
authors.initials: F
authors.lastname: Guérault
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity