Segmentation-based tracking of macrophages in 2D＋time microscopy movies inside a living animal.

The automated segmentation and tracking of macrophages during their migration are challenging tasks due to their dynamically changing shapes and motions. This paper proposes a new algorithm to achieve automatic cell tracking in time-lapse microscopy macrophage data. First, we design a segmentation method employing space-time filtering, local Otsu's thresholding, and the SUBSURF (subjective surface segmentation) method. Next, the partial trajectories for cells overlapping in the temporal direction are extracted in the segmented images. Finally, the extracted trajectories are linked by considering their direction of movement. The segmented images and the obtained trajectories from the proposed method are compared with those of the semi-automatic segmentation and manual tracking. The proposed tracking achieved 97.4% of accuracy for macrophage data under challenging situations, feeble fluorescent intensity, irregular shapes, and motion of macrophages. We expect that the automatically extracted trajectories of macrophages can provide pieces of evidence of how macrophages migrate depending on their polarization modes in the situation, such as during wound healing.

Exploring Natura 2000 habitats by satellite image segmentation combined with phytosociological data: a case study from the Cierny Balog area (Central Slovakia).

Natura 2000 is a network of protected areas covering Europe's most valuable and threatened species and habitats. Recently, biota belonging to these networks have been threatened by both climate change and various human impacts. Regular monitoring is needed to ensure effective protection and proper management measures in these sites and habitats, but conventional field approaches are often time-consuming and inaccurate. New approaches and studies with different focuses and results are being developed. Our approach includes point data from field research and phytosociological databases as starting points for automatic segmentation, which has been developed just recently as a novel method that could help to connect ground-based and remote sensing data. Our case study is located in Central Slovakia, in the mountains around the village of Cierny Balog. The main aim of our case study is to apply advanced remote sensing techniques to map the area and condition of vegetation units. We focus on forest habitats belonging mainly to the Natura 2000 network. We concentrated on the verification of the possibilities of differentiation of various habitats using only multispectral Sentinel-2 satellite data. Our software NaturaSat created by our team was used to reach our objectives. After collecting data in the field using phytosociological approach and segmenting the explored areas in the program NaturaSat, spectral characteristics were calculated within identified habitats using software tools, which were subsequently processed and tested statistically. We obtained significant differences between forest habitat types. Also, segmentation accuracy was tested by comparing closed planar curves of ground based filed data and software results. This provided promising results and validation of the methods used. The results of this study have the potential to be used in a wider area to map the occurrence and quality of Natura 2000 habitats.

Macrophages undergo a behavioural switch during wound healing in zebrafish.

In response to wound signals, macrophages are immediately recruited to the injury where they acquire distinct phenotypes and functions, playing crucial roles both in host defense and healing process. Although macrophage phenotypes have been intensively studied during wound healing, mostly using markers and expression profiles, the impact of the wound environment on macrophage shape and behaviour, and the underlying mechanisms deserve more in-depth investigation. Here, we sought to characterize the dynamics of macrophage recruitment and behaviour during aseptic wounding of the caudal fin fold of the zebrafish larva. Using a photo-conversion approach, we demonstrated that macrophages are recruited to the wounded fin fold as a single wave where they switch their phenotype. Intravital imaging of macrophage shape and trajectories revealed that wound-macrophages display a highly stereotypical set of behaviours and change their shape from amoeboid to elongated shape as wound healing proceeds. Using a pharmacological inhibitor of 15-lipoxygenase and protectin D1, a specialized pro-resolving lipid, we investigated the role of polyunsaturated fatty acid metabolism in macrophage behaviour. While inhibition of 15-lipoxygenase using PD146176 or Nordihydroguaiaretic acid (NDGA) decreases the switch from amoeboid to elongated shape, protectin D1 accelerates macrophage reverse migration and favours elongated morphologies. Altogether, our findings suggest that individual macrophages at the wound switch their phenotype leading to important changes in behaviour and shape to adapt to changing environment, and highlight the crucial role of lipid metabolism in the control of macrophage behaviour plasticity during inflammation in vivo.

Distribution of neurosensory progenitor pools during inner ear morphogenesis unveiled by cell lineage reconstruction.

Reconstructing the lineage of cells is central to understanding how the wide diversity of cell types develops. Here, we provide the neurosensory lineage reconstruction of a complex sensory organ, the inner ear, by imaging zebrafish embryos in vivo over an extended timespan, combining cell tracing and cell fate marker expression over time. We deliver the first dynamic map of early neuronal and sensory progenitor pools in the whole otic vesicle. It highlights the remodeling of the neuronal progenitor domain upon neuroblast delamination, and reveals that the order and place of neuroblasts' delamination from the otic epithelium prefigure their position within the SAG. Sensory and non-sensory domains harbor different proliferative activity contributing distinctly to the overall growth of the structure. Therefore, the otic vesicle case exemplifies a generic morphogenetic process where spatial and temporal cues regulate cell fate and functional organization of the rudiment of the definitive organ.

A workflow to process 3D+time microscopy images of developing organisms and reconstruct their cell lineage.

The quantitative and systematic analysis of embryonic cell dynamics from in vivo 3D+time image data sets is a major challenge at the forefront of developmental biology. Despite recent breakthroughs in the microscopy imaging of living systems, producing an accurate cell lineage tree for any developing organism remains a difficult task. We present here the BioEmergences workflow integrating all reconstruction steps from image acquisition and processing to the interactive visualization of reconstructed data. Original mathematical methods and algorithms underlie image filtering, nucleus centre detection, nucleus and membrane segmentation, and cell tracking. They are demonstrated on zebrafish, ascidian and sea urchin embryos with stained nuclei and membranes. Subsequent validation and annotations are carried out using Mov-IT, a custom-made graphical interface. Compared with eight other software tools, our workflow achieved the best lineage score. Delivered in standalone or web service mode, BioEmergences and Mov-IT offer a unique set of tools for in silico experimental embryology.

Automated processing of zebrafish imaging data: a survey.

Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines.

New robust algorithm for tracking cells in videos of Drosophila morphogenesis based on finding an ideal path in segmented spatio-temporal cellular structures.

In this paper, we present a novel algorithm for tracking cells in time lapse confocal microscopy movie of a Drosophila epithelial tissue during pupal morphogenesis. We consider a 2D + time video as a 3D static image, where frames are stacked atop each other, and using a spatio-temporal segmentation algorithm we obtain information about spatio-temporal 3D tubes representing evolutions of cells. The main idea for tracking is the usage of two distance functions--first one from the cells in the initial frame and second one from segmented boundaries. We track the cells backwards in time. The first distance function attracts the subsequently constructed cell trajectories to the cells in the initial frame and the second one forces them to be close to centerlines of the segmented tubular structures. This makes our tracking algorithm robust against noise and missing spatio-temporal boundaries. This approach can be generalized to a 3D + time video analysis, where spatio-temporal tubes are 4D objects.

Cells segmentation from 3-D confocal images of early zebrafish embryogenesis.

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.

Segmentation of cells from 3-D confocal images of live zebrafish embryo.

In this paper, we use partial-differential-equation-based segmentation to accurately extract the shapes of membranes and nuclei from time lapse confocal microscopy images, taken throughout early Zebrafish embryogenesis. This strategy is a prerequisite for an accurate quantitative analysis of cell shape and morphodynamics during organogenesis and is the basis for an integrated understanding of biological processes. This data will also serve for the measurement of the variability between individuals in a population. The segmentation of cellular structures is achieved by first using an edge-preserving image filtering method for noise reduction and then applying an algorithm for cell shape reconstruction based on the Subjective Surfaces technique.

3-D zebrafish embryo image filtering by nonlinear partial differential equations.

We discuss application of nonlinear PDE based methods to filtering of 3-D confocal images of embryogenesis. We focus on the mean curvature driven and the regularized Perona-Malik equations, where standard as well as newly suggested edge detectors are used. After presenting the related mathematical models, the practical results are given and discussed by visual inspection and quantitatively using the mean Hausdorff distance.

Cells tracking in a live zebrafish embryo.

We designed a set of procedures for achieving the tracking of cell nuclei and the identification of cell divisions in live zebrafish embryos using 3D+time images acquired by confocal laser scanning microscopy (CLSM). Our strategy includes image signal enhancement with feature preserving denoising algorithm, automated identification of the nuclei position, extraction of the optical flow from 3D images sequences and tracking of nuclei.

Evolutionary partial differential equations for biomedical image processing.

We are presenting here a model for processing space-time image sequences and applying them to 3D echo-cardiography. The non-linear evolutionary equations filter the sequence with keeping space-time coherent structures. They have been developed using ideas of regularized Perona-Malik an-isotropic diffusion and geometrical diffusion of mean curvature flow type (Malladi-Sethian), combined with Galilean invariant movie multi-scale analysis of Alvarez et al. A discretization of space-time filtering equations by means of finite volume method is discussed in detail. Computational results in processing of 3D echo-cardiographic sequences obtained by rotational acquisition technique and by real-time 3D echo volumetrics acquisition technique are presented. Quantitative error estimation is also provided.