Denoising 3D microscopy images of cell nuclei using shape priors on an anisotropic grid

This paper presents a new multiscale method to denoise three-dimensional images of cell nuclei. The speci- ficity of this method is its awareness of the noise distribution and object shapes. It combines a multiscale representation called Isotropic Undecimated Wavelet Transform (IUWT) with a nonlinear transform, a statistical test and a variational method, to retrieve spherical shapes in the image. Beyond extending an existing 2D approach to a 3D problem, our algorithm takes the sampling grid dimensions into account. We compare our method to the two algorithms from which it is derived on a representative image analysis task, and show that it is superior to both of them. It brings a slight improvement in the signal-to-noise ratio and a significant improvement in cell detection

Counting number of cells and cell segmentation using advection-diffusion equations

summary:We develop a method for counting number of cells and extraction of approximate cell centers in 2D and 3D images of early stages of the zebra-fish embryogenesis. The approximate cell centers give us the starting points for the subjective surface based cell segmentation. We move in the inner normal direction all level sets of nuclei and membranes images by a constant speed with slight regularization of this flow by the (mean) curvature. Such multi- scale evolutionary process is represented by a geometrical advection-diffusion equation which gives us at a certain scale the desired information on the number of cells. For solving the problems computationally we use flux-based finite volume level set method developed by Frolkovič and Mikula in [FM1] and semi-implicit co-volume subjective surface method given in [CMSSg, MSSgCVS, MSSgchapter]. Computational experiments on testing and real 2D and 3D embryogenesis images are presented and the results are discussed

Quantification of cell behaviors and computational modelling show that cell directional behaviors drive zebrafish pectoral fin morphogenesis

Motivation: Understanding the mechanisms by which the zebrafish pectoral fin develops is expected to produce insights on how vertebrate limbs grow from a 2D cell layer to a 3D structure. Two mechanisms have been proposed to drive limb morphogenesis in tetrapods: a growth-based morphogenesis with a higher proliferation rate at the distal tip of the limb bud than at the proximal side, and directed cell behaviors that include elongation, division and migration in a nonrandom manner. Based on quantitative experimental biological data at the level of individual cells in the whole developing organ, we test the conditions for the dynamics of pectoral fin early morphogenesis. Results: We found that during the development of the zebrafish pectoral fin, cells have a preferential elongation axis that gradually aligns along the proximodistal axis (PD) of the organ. Based on these quantitative observations, we build a center-based cell model enhanced with a polarity term and cell proliferation to simulate fin growth. Our simulations resulted in 3D fins similar in shape to the observed ones, suggesting that the existence of a preferential axis of cell polarization is essential to drive fin morphogenesis in zebrafish, as observed in the development of limbs in the mouse, but distal tip-based expansion is not. Availability: Upon publication, biological data will be available at http://bioemergences.eu/modelingFin, and source code at https://github.com/guijoe/MaSoFin. Contact: [email protected], [email protected] or [email protected] Supplementary information: Supplementary data are included in this manuscript

Recording and statistical analysis of early zebrafish developmental patterns using in vivo multiphoton microscopy.

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Reconstructing multiscale dynamics in vertebrate morphogenesis

International audienceA complete understanding of early morphogenetic processes has been an elusive goal. For most of the last century quantifying cellular behavior and motion patterns presented a formidable technical challenge. More recently, the availability of modern optics, ingenious software and reasonably priced computers has begun to revolutionize embryology. We designed a framework for imaging and reconstructing deep focus images of whole zebrafish embryos during early morphogenetic stages with minimal experimental manipulation. Our approach records time and distance measurements along with cell lineage analysis at micrometer spatial resolution and minute-level temporal accuracy. The automated image processing methodology extracts membrane geometry and cell positional fate information while monitoring mitosis synchrony. The analyses are conducted on entire embryos and the resulting data provide a realistic quantitative multi-scale ensemble view of morphogenetic mechanisms. Our global approach to dynamical understanding of embryogenesis establishes rigorous standards of measurement precision and the accuracy of automated segmentation and tracking procedures. It is expected that these in vivo data will provide a foundation for further analysis of the interplay between molecular, cellular and tissue level dynamics during formation of vertebrate embryos

Towards 3D in silico modeling of the sea urchin embryonic development.

International audienceEmbryogenesis is a dynamic process with an intrinsic variability whose understanding requires the integration of molecular, genetic, and cellular dynamics. Biological circuits function over time at the level of single cells and require a precise analysis of the topology, temporality, and probability of events. Integrative developmental biology is currently looking for the appropriate strategies to capture the intrinsic properties of biological systems. The "-omic" approaches require disruption of the function of the biological circuit; they provide static information, with low temporal resolution and usually with population averaging that masks fast or variable features at the cellular scale and in a single individual. This data should be correlated with cell behavior as cells are the integrators of biological activity. Cellular dynamics are captured by the in vivo microscopy observation of live organisms. This can be used to reconstruct the 3D + time cell lineage tree to serve as the basis for modeling the organism's multiscale dynamics. We discuss here the progress that has been made in this direction, starting with the reconstruction over time of three-dimensional digital embryos from in toto time-lapse imaging. Digital specimens provide the means for a quantitative description of the development of model organisms that can be stored, shared, and compared. They open the way to in silico experimentation and to a more theoretical approach to biological processes. We show, with some unpublished results, how the proposed methodology can be applied to sea urchin species that have been model organisms in the field of classical embryology and modern developmental biology for over a century

Cell tracking of development using 2-photon scanning and light sheet imaging

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Conversion of zebrafish blastomeres to an endodermal fate by TGF-β-related signalling

International audienceThe endoderm contributes cells to the gut, and participates in the induction and patterning of the vertebrate head and heart. The mechanisms controlling the formation of endoderm are poorly understood. Commitment of endoderm cells occurs at the onset of gastrulation and requires cell interactions; studies in vitro have implicated transforming growth factor Beta (TGF-beta)-related molecules in this process. TARAM-A is a zebrafish receptor kinase that is related to the type I subunit of the TGF-beta receptor, and is expressed in presumptive endomesodermal cells at gastrulation. We provide here evidence for its involvement in endoderm formation in vivo. Activation of TARAM-A was found to drive blastomeres towards an endodermal fate. The induced endoderm behaved ad endogenous endoderm during gastrulation: it migrated in contact with the yolk and expressed endoderm-specific markers. Loss-of-function mutations in the zebrafish one-eyed-pinhead (OEP) gene lead to defects in heart formation, defects of the ventral central nervous system (CNS) and cyclopia. Mutant embryos also lack endoderm and anterior mesoderm. Endoderm formation in oep mutant embryos was found to be restored by the activation of the TARAM-A signaling pathway. Cardiac and ocular defects, but not midline CNS structures, were rescued non-autonomously, demonstrating that endoderm may provide signals that can pattern the eye anlage, and which are distinct form those specifying the ventral midline of the CNS

The Nonlinear Tensor Diffusion in Segmentation of Meaningful Biological Structures from Image Sequences of Zebrafish Embryogenesis

2nd International Conference on Scale Space and Variational Methods in Computer Vision, Voss, NORWAY, JUN 01-05, 2009International audienceIn this contribution we develop a strategy for segmentation of evolving biological structures in image sequences. Our approach is based on combination of nonlinear tensor diffusion image smoothing and subjective surface based image segmentation. Since the fine cell structure would restrain the evolving segmentation function to achieve a shape of meaningful biological structures, we have to smooth properly the images in the sequence. To that goal we apply the nonlinear tensor diffusion which enhances the connectivity of bordering structure lines and smoothes their inner parts. For the numerical implementations we use semi-implicit diamond-cell finite volume methods both for filtering and segmentation. We show application of the method in image segmentation of early stages of zebrafish embryogenesis

Numerical algorithm for tracking cell dynamics in 4D biomedical images

International audienceThe paper presents new numerical algorithm for an automated cell tracking from large-scale 3D+time two-photon laser scanning microscopy images of early stages of zebra sh (Danio rerio) embryo development. The cell trajectories are extracted as centered paths inside segmented spatio-temporal tree structures representing cell movements and divisions. Such paths are found by using a suitably designed and computed constrained distance functions and by a backtracking in steepest descent direction of a potential eld based on these distance functions combination. The naturally parallelizable discretization of the eikonal equation which is used for computing distance functions is given and results of the tracking method for real 4D image data are presented and discussed