Combining sea urchin embryo cell lineages by error-tolerant graph matching.

Obtaining the complete cell lineage tree of an embryo's development is a very appealing and ambitious goal, but fortunately recent developments both in optical imaging and digital image processing are bringing it closer. However, when imaging the embryos (sea urchin embryos for this work) with high enough spatial resolution and short enough time-step to make cell segmentation and tracking possible, it is currently not possible to image the specimen throughout its all embryogenesis. For this reason it is interesting to explore how cell lineage trees extracted from two different embryos of the same species and imaged for overlapping periods of time can be concatenated, resulting in a single lineage tree covering both embryos' development time frames. To achieve this we used an error-tolerant graph matching strategy by selecting a time point at which both lineage trees overlap, and representing the information about each embryo at that time point as a graph in which nodes stand for cells and edges for neighborhood relationships among cells. The expected output of the graph matching algorithm is the minimal-cost correspondence between cells of both specimens, allowing us to perform the lineage combination.

Cell tracking in fluorescence images of embryogenesis processes with morphological reconstruction by 4D-tubular structuring elements.

We present a simple and parameter-free nuclei tracking method for reconstructing cell dynamics in fluorescence 3D+t images of embryogenesis. The strategy is based on the use of the mathematical morphology operators directly in the 4D image. The morphological reconstruction of a marker -manually or automatically selected- in an initial spatio-temporal position generates a connected path over the time representing the cell migration. Thus, the processing provides a coherent spatiotemporal estimation of cell movement. The algorithm has been validated on in vivo images of early zebrafish and sea urchin embryogenesis acquired with two-photon laser scanning microscopy providing mean tracking rates above 98% per time step.

An automatic quantification and registration strategy to create a gene expression atlas of zebrafish embryogenesis.

In order to properly understand and model the gene regulatory networks in animals development, it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains. In this paper, we propose a complete computational framework to fulfill this task and create a 3D Atlas of the early zebrafish embryogenesis annotated with both the cellular localizations and the level of expression of different genes at different developmental stages. The strategy to construct such an Atlas is described here with the expression pattern of 5 different genes at 6 hours of development post fertilization.