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Caenorhabditis elegans is an important model organism for the study of molecular mechanisms of development and disease processes, due to its well-known genome and invariant cell lineage tree. Such studies generally produce vast amounts of image data, and require very robust and efficient algorithms to extract and characterize lineage phenotypes and to determine gene expression patterns. Previously...
The ultimate aim of many live-cell fluorescence microscopy imaging experiments is the quantitative analysis of the spatial structure and temporal behavior of intracellular objects. This requires finding the precise geometrical correspondence between the time frames for each individual cell and performing intracellular segmentation. In a previous paper we have developed a powerful multi-level-set based...
Segmentation and tracking of cells in fluorescence microscopy image sequences is an important task in many biological studies into cell migration as well as intracellular dynamics. The growing size and complexity of biological image data sets precludes manual analysis, and calls for increasingly advanced automatic algorithms that are generic enough to be easily tunable to different applications, yet...
Quantifying the motion and deformation of large numbers of cells through image sequences obtained with fluorescence microscopy is a recurrent task in many biological studies. Automated segmentation and tracking methods are increasingly needed to be able to analyze the large amounts of image data acquired for such studies. In addition, automated techniques have the possibility to improve sensitivity,...
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