We designed a strategy for extracting the shapes of cell membranes and nuclei from time lapse confocal images taken throughout early zebrafish embryogenesis using a partial-differential-equation-based segmentation. This segmentation step is a prerequisite for an accurate quantitative analysis of cell morphodynamics during embryogenesis and it is the basis for an integrated understanding of biological processes. The segmentation of embryonic cells requires live zebrafish embryos fluorescently labeled to highlight sub-cellular structures and designing specific algorithms by adapting classical methods to image features. Our strategy includes the following steps: the signal-to-noise ratio is first improved by an edge-preserving filtering, then the cell shape is reconstructed applying a fully automated algorithm based on a generalized version of the Subjective Surfaces technique. Finally we present a procedure for the algorithm validation either from the accuracy and the robustness perspective.

We introduce a new model for multiscale analysis of space-time echocardiographic sequences. The proposed nonlinear partial differential equation, representing the multiscale analysis, filters the sequence while keeping the space-time coherent structures. It combines the ideas of regularized Perona-Malik anisotropic diffusion and the Galilean invariant movie multiscale analysis of Alvarez, Guichard, Lions and Morel. A numerical method for solving the proposed partial differential equation is suggested and its stability is shown. Computational results on synthesized and real sequences are provided. A qualitative and quantitative evaluation of the accuracy of the method is presented.