A Two-Step Area Based Method for Automatic Tight Segmentation of Zona Pellucida in HMC Images of Human Embryos

An important prognostic parameter for assessing the success of an in vitro fertilization treatment is the variation in thickness of the zona pellucida. Zona pellucida, the envelope of the human embryo, is usually visualized using Hoffman modulation contrast microscopy (HMC). This paper considers automatic segmentation of zona pellucida in HMC images of human embryos. There are two subproblems: (a) the embryo should be separated from the background and (b) the zona should be separated from the rest of the embryo. (a) is solved using a robust formulation of a classical area based method and (b) is solved using a probabilistic method. Both solutions are set in a variational framework using a novel image model for the zona. This variational framework is adapted to handle images in which large artefacts are covered with masks. Since the zona has a simple topology we focus on parametric models and a representation by trigonometric sums is considered.