A Variational Framework for Active and Adaptative Segmentation of Vector Valued Images
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Automatic Segmentation of Zona Pellucida in HMC Images of Human Embryos
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Reconstructing the optical thickness from Hoffman modulation contrast images
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Detection and localization of random signals
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
IEEE Transactions on Image Processing
Lighting-Aware Segmentation of Microscopy Images for In Vitro Fertilization
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
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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.