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Analyzes, processes and visualizes multi-dimensional microscopy images. BioImageXD puts open-source computer science tools for three-dimensional visualization and analysis into the hands of all researchers, through a user-friendly graphical interface tuned to the needs of biologists. BioImageXD has no restrictive licenses or undisclosed algorithms and enables publication of precise, reproducible and modifiable workflows. It allows simple construction of processing pipelines and should enable biologists to perform challenging analyses of complex processes.
Allows representation of multidimensional cellular measurements. PhenoPlot is a toolbox that permits visualization of up to 21 variables. It may be useful for determining the morphology of breast cancer cell lines or for understanding and interpreting multidimensional cellular imaging data. To assist users, this tool employs many visual elements such as differently sized, coloured and structured objects. It provides effective and intuitive pictorial representations of cellular phenotypes.
A simple and user-friendly ImageJ plugin dedicated to the characterization of nuclear morphology and chromatin organization in 3D. Starting from image stacks, the nuclear boundary is delimited by combining the Otsu segmentation method with optimization of nuclear sphericity. Chromatin domains are segmented by partitioning the nucleus using a 3D watershed algorithm and by thresholding a contrast measure over the resulting regions. As output, NucleusJ quantifies 15 parameters including shape and size of nuclei as well as intra-nuclear objects and their position within the nucleus.
Retrieves diverse shortest paths between two end-points. DiversePathsJ returns paths that can then be swiftly browsed and displayed on the image using the arrow keyboard keys, or exported in generic formats for further processing. It allows users to analyze multiple instances of the same objects exhibiting slight variations without the need for fine-tuning of the cost function. This tool is not restricted to quantitative estimation of shape features such as length and bending. It covers every problem in which a path is to be searched between two end-points.
A wavelet-based image-analysis software providing a fast automatic detection scheme for circular patterns (spots), combined with the precise estimation of their size. SpotCaliper is able to automatically find spots of varying size, and gives a precise measurement on their radius. The detections are collected in a table, displaying the following parameters: unique identifier (ID) of the spot, its location (x and y coordinates), radius, confidence, contrast, SNR and type. It is implemented as an ImageJ plugin with a friendly user interface. The user is allowed to edit the results by modifying the measurements (in a semi-automated way), extract data for further analysis. The fine tuning of the detections includes the possibility of adjusting or removing the original detections, as well as adding further spots. The main advantage of the software is its ability to capture the size of spots in a fast and accurate way.
Enables cell lineage tracking. MicrobeTracker utilizes cell shape and timelapse information to achieve cell outlining. It can track fluorescently labeled molecules in cell lineages over several generations or in difficult-to-resolve samples, such as densely-packed or filamentous cells, from time-lapse sequences. This tool is delivered with an accessory tool, called SpotFinder, that detects small round spots, generating precise cell coordinates of fluorescently labeled foci inside cells.
FMAj / Fly Muscle Analysis in Java
Performs quantitative characterization of muscle phenotypes in time-series images. FMAj is composed of three modules: (i) the first one captures experimental metadata derived from the images or via manual annotation by the user; (ii) the second performs segmentation of muscle cells and nuclei in a semi-automated fashion.; (iii) the third module achieves comparative phenotypic analysis, such as comparing the cell morphology between control and genetically perturbed cells.
A high throughput method to automatically detect the transition of a cell cluster from two to three cells in thousands of videos. livespin performs a robust implicit tracking of cells even when they are packed, overlap or are not clearly distinguishable. The approach is based on a robust fitting of two-dimensional Gaussian mixture models with two and three components on each frame of the video. livespin is composed of four steps described in this section. The first step consists in localizing the fibronectin patterns and cropping the whole video at those locations to obtain individual cluster sequences, the second step consists in fitting 2- and 3-components Gaussian mixture model (GMM) onto each frame of each video sequence and the third step consists in the identification of the first frame containing three cells (the transition from 2 cells to 3 cells) using the fitting error difference and other features computed from the GMM parameters. The final step consists in the computation of the angle of division in the identified frame.
BCOMS / Biologically Constrained Optimization based cell Membrane Segmentation
Automates cell shape extraction in C. elegans embryos. BCOMS provides a user-friendly framework that computerizes not only the segmentation process but also the evaluation process. The performance of BCOMS was validated by comparisons with the ground truth and by comparing the results in two adjacent time points. This method is also applicable to other model organisms by customizing the biological constraints.
Assesses the effects of disruption of a given protein on the mitotic spindle. MatQuantify is a standalone software that allows users to identify structural changes in spindle or DNA and can be applied to fluorescence microscopy images for measuring: (i) physical properties, including perimeter, fractal dimension or satellite objects; and (ii) textual properties, such as entropy, intensities and their standard deviation. The application can detect both fine and large-scale changes.
An easy to use software application that will greatly speed and standardize quantification of neuron organization. IPLaminator rapidly analyzes neurite stratification patterns in the retina and other neural tissues. A range of user options allows researchers to bin inner plexiform layer (IPL) stratification based on fixed points, such as the neurites of cholinergic amacrine cells, or to define a number of bins into which the IPL will be divided. Options to analyze tissues such as cortex were also added. Statistical analysis of the output then allows a quantitative value to be assigned to differences in laminar patterning observed in different models, genotypes or across developmental time.
Allows determination of the number of foci in a single cell, a focus intensity per cell, as well as a cell intensity. FociCounter was tested by analysing gamma-H2AX foci in CHO and MO59K cells irradiated in vitro with X-rays. It was validated by comparing the results obtained with the outcome of automated image analysis and flow cytometry. The software was developed for research laboratories possessing a fluorescent microscope in combination with a digital camera. FociCounter was designed for the most common image formats that are two-dimensional.
A MATLAB based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. CellSegm has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classification of cell candidates. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in MATLAB, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening.
Automating Morphological Profiling with Generic Deep Convolutional Networks
Uses deep feature transfer for generating morphological profiles without human interaction. Automating Morphological Profiling with Generic Deep Convolutional Networks achieves higher accuracies than previous classical methods, needs less time and expertise to extract profiles and allows for true automated high content screening by taking the human out of the loop. Furthermore, it enables fully automated processing of microscopy images without need for single cell identification.
SMASH / Semi-automatic Muscle Analysis using Segmentation of Histology
Provides an automatic and standardized image segmentation platform. SMASH permits users to measure multiple facets of muscle histology. It carries a high monetary cost and is not specifically designed for skeletal muscle analysis. This tool generates results validated against legacy methods showing largely consistent results between methods for fiber type and centrally nucleated fiber (CNF) percentages. It reduces the border region between adjacent fibers, it is also capable of delineating interstitial space between adjacent fibers when there is an appreciable separation.
Amira 3D Software for Life Sciences
Allows users to visualize, manipulate, and understand data from imaging modalities such as computed tomography, microscopy or Magnetic resonance imaging (MRI). Amira 3D Software for Life Sciences provides features to import and process 2D and 3D images data, visualization techniques and tools for visual analysis. Users can also create and share presentations. The base product can be customized by adding functional extensions to fit special needs in different application areas.
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