Processes quantitative analyses of high throughput cell migration assay. WIS-PhagoTracker facilitates morphometric analysis of modified Phagokinetic tracks that are visualized by using a screening microscope. This software applies a multi-scale segmentation algorithm to characterize several morphometric parameters such track area, perimeter, major and minor axis and solidity for each track. It can support single image files and run batch processing of multiple plates.
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 the detection of cells, the creation of seeds and boundaries for the automatic segmentation of cell geometries. Balloon Segmentation is an algorithm implemented as a Java ImageJ plugin assisting users in the analysis of images. It enables the measurement of cellular properties in intact tissue while retaining the cellular context for subsequent studies.
Consists of a cloud based deep learning solution for image segmentation of light, electron and X-ray microscopy. CDeep3M serves for image segmentation tasks of large and complex 2D and 3D microscopy datasets by taking advantage of the underlying architecture of a deep learning convolutional neural network (CNN) called DeepEM3D. This software is also available on the Amazon Web Services (AWS) platform.
Performs crowd-based images annotation. Quanti.us is a portal that assists users in recruiting groups of untrained Mechanical Turk workers (Turkers) to annotate images using a set of interaction tools. The platform enables uploading of image sets, selection of an analysis tool, and provides sets of instructions. Users can gather hand annotations by marshaling paid Turkers to annotate a range of image types. Quanti.us thus makes crowd analysis of scientific images applicable to several annotation problems.
A tool for segmentation, fluorescence quantification, and tracking of cells on microscopy images. CellX decodes the information across the cell membrane and guarantees optimal detection of the cell boundaries on a per-cell basis. Graph cuts account for the information of the cell boundaries through directional cross-correlations, and they automatically incorporate spatial constraints. The method accurately segments images of various cell types grown in dense cultures that are acquired with different microscopy techniques.
Serves for effective segmentation of multidimensional datasets. MIB can recognize several number of imaging formats and offers a variety of image processing tools. It also simplifies utilization and quantification of acquired data. It permits users to segment large datasets, to realize 3D visualization, and to quantify images and models. Its parameters enable users to insert plugin s to customize the program for specific needs.
Allows analysis of epithelial tissues. EpiTools automates image analysis including cell segmentation and cell tracking. It describes dynamic cellular behavior and allows users to study the power of in vivo imaging. This tool supplies a graphical user interface to simplify its utilization by users and for segmenting and tracking the contours of cell membrane signals obtained from 4D confocal imaging. It is intended primarily for biologists with no computer-science background.
Provides general purpose functionality for reading, writing, processing and analysis of images. In the context of microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. This allows the automation of such tasks using the R programming language and use of existing tools in the R environment for signal processing, statistical modeling, machine learning and data visualization. It uses ImageMagick to read and save images, and supports more than 80 image formats, including JPEG, TIFF, TGA, GIF and PNG. EBImage also supports standard geometric transformations such as rotation, reflection, cropping, translation and resizing. Classical image processing tools are available: linear filtering, morphological erosion and dilation, fast distance map computation, contour delineation and area filling.
Provides assistance for visualization and analysis of multi-modal, multi-process and time-lapse microscopy morphological and functional images at single-cell level. SCIP can execute an automatic or manually corrected segmentation of cells and lineages, automatic alignment of different microscopy channels and identify, measure and determine fluorescent spots. This software aims to ease the finding of relationships between cellular processes from small-scale to large-scale in single cells and cell lineages.
Consists of a high-throughput single-cell imaging and image processing protocol. TIMING conducts large-scale automated video array investigations. It can construct quantitative analyses of cell interaction behaviors at single-cell resolution with visual confirmation. This tool counts the cells in each nanowell, finds their types based on cell-type markers, and provides measurements of size, location, shape, and movements of cells.
Segments and tracks budding yeast cells. DISCO is a comprehensive framework structured into several stages for integrated identification, segmentation and tracking of cells: (i) identification of physical features of the microfluidic device, (ii) supervised classification to identify cell centers, (iii) segmentation using a morphologically constrained cell-shape model, (iv) incorporation of temporal information to refine cell center prediction and (v) iterative greedy optimization of cell contours.
Assists in analyzing white adipose tissue cellularity in histological sections. Adiposoft automates the analysis of histological adipose tissue samples and requires a single click to analyze a whole set of images. This tool works with standard histological sections, whereas the analysis of cells in suspension requires collagenase digestion of the adipose tissue sample.
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.
Segments touching cells in 2D images. iCut provides an integrative cut algorithm merging information about spatial location and the intervening and concave contours. It aims to facilitate high-throughput analysis of brain anatomy by using massive image datasets and to afford the automatic and precise segmentation of touching cells. It was tested with both simulated and experimental image datasets.
Provides assistance for distance analysis and object-based 3D co-localization. DiAna incorporates two 3D procedures for image segmentation and 3D automated object-based co-localization in-depth analysis. It measures the distribution of distances between objects in 3D. This software allows users to label images and provides features tools for the segmentation of the objects and extended functionalities for 3D distance analysis and 3D measurements.
It is an organized collection of software modules for image data handling, pre-processing, segmentation, inspection and editing, post-processing, and secondary analysis. These modules can be scripted to accomplish a variety of automated image analysis tasks.
Allows users to detect and count fluorescent signals in microscopy images of cells. Blob Finder is a free software that performs two types of analysis: (i) an average count, for quantifying the number of nuclei and signals in an image; (ii) and a single cell analysis, that assigns each signal to the closest cell and get a signal count for each cell in the image. It also performs on-z_stacks of the cell with a maximum projection to project the image data into a 2D image.
A three-dimensional (3D) reconstruction and modeling software. Free-D allows to generate, process and analyze 3D point and surface models from stacks of 2D images. It is an integrated software tool, offering in a single graphical user interface all the functionalities required for 3D modeling.
An automated algorithm for 3D cell nuclei segmentation based on gradient flow tracking. The proposed algorithm is able to segment closely juxtaposed or touching cell nuclei obtained from 3D microscopy imaging with reasonable accuracy. To validate the efficacy and performance of the proposed segmentation algorithm, we evaluated it by using synthesized and real biological images. The results show that the algorithm is able to segment juxtaposed nuclei correctly, a persistent problem in the field of cellular image analysis.
An automated segmentation method that accurately separates cells when confluent and touching each other. This technique is successfully applied to phase contrast, bright field, fluorescence microscopy and binary images. The method is based on morphological watershed principles with two new features to improve accuracy and minimize over-segmentation. First, FogBank uses histogram binning to quantize pixel intensities which minimizes the image noise that causes over-segmentation. Second, FogBank uses a geodesic distance mask derived from raw images to detect the shapes of individual cells, in contrast to the more linear cell edges that other watershed-like algorithms produce.
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.
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.
Segments packed cells while quantifying protein clusters by using a single fluorescent marker. SegmentMe is a click and-drag software dedicated to the processing of protein clusters dynamics. The application exists as a 2D projection version as well as in 3D. The application is divided into a processing and an analysis panel and includes features for three-frame time or spatial averaging.
Allows to realize automatic segmentation of overlapping cells. Anglegram identifies junctions between the boundaries of overlapping objects based on the angles between points of the overlapping boundary. This algorithm is a 2D matrix multiscale angle variation that can be used to discover junctions of overlapping cells. It was tested with synthetic data and fluorescently labelled macrophages observed on embryos of Drosophila melanogaster.
Assists in segmentation of fluorescence microscope images of punctate patterns. Active Mask Segmentation Plugin is an extension from the algorithm termed active mask segmentation developed as a module usable through the ImageJ software. It uses four types of methods including active-contour, multiresolution, multiscale and region-growing methods with the aim of increasing the speed and the flexibility.
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.
Captures the mass spectrometry (MS) lesion spatial distribution and identifies lesions regardless of their orientation, shape or size. RMNMS detects MS lesions using a training library containing T2-weighted (T2W) and FLAIR images along with manual T2W lesion masks. Moreover, it assists users in the detection of presence of lesions as lesion-wise measures.
Segments nearly elliptic objects via parametric active contour. E-Snake applies an active contour (named snake) segmentation method by using exponential splines as basis functions to represent the outline of the shape. This ImageJ plugin emulates elliptical and circular shapes and can produce an approximation of any closed curve in the plane. These proprieties can be useful to delineate cross sections of cylindrical-like conduits and to outline blob-like objects.
Provides high content quantification of muscle features. MyoVision includes fiber number, cross sectional area (CSA), minimum Feret diameter, myonuclear number, and fiber type distribution, without requiring human supervision. It separates connected muscle fibers using the efficient watershed transformation and then fine-tunes the cytoplasmic boundaries using the active contour method. This tool is able to eliminate inter-individual variation.
Discovers the “classical” endpoints neuron quantification and neuronal morphology but also novel endpoints like radial migration and neuronal density distributions within the Neurosphere Assay. Omnisphero aims to automated high-content image analysis (HCA) developmental neurotoxicity (DNT) screenings. It can be applied in other 3D in vitro systems such as in the migration assay of tumor spheroids.
Provides an image analysis-based myelin sheath detection application. DeepMQ is an algorithm that consists of a feature extraction step with a deep learning based binary classification module. The images are acquired on a confocal microscope that contain three channels and multiple z-sections. Each channel represents either oligodendroyctes, neurons, or nuclei.
Provides an image analysis software for prokaryotes with complex morphologies. BacStalk is an application specialized for automated, label-free, time-resolved image analysis of stalked and non-stalked bacteria. It enables the detection of fluorescence patterns and the morphometric analysis of cell bodies, and their corresponding stalks and buds. It can also visualize fluorescence signals in cells in interactive demographs and kymographs.
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.
A simple, user-friendly tool for interactive image classification, segmentation and analysis. It is built as a modular software framework, which currently has workflows for automated (supervised) pixel- and object-level classification, automated and semi-automated object tracking, semi-automated segmentation and object counting without detection. Most analysis operations are performed lazily, which enables targeted interactive processing of data subvolumes, followed by complete volume analysis in offline batch mode.
Consists of a classification plugin for ImageJ. ImageSURF uses standard bitmap formats for: (1) class annotations, (2) making the training process open, repeatable and (3) incorporating large training sets created by multiple users across multiple sessions with the software of their choice. This tool utilizes primitive data structures to avoid the substantial overheads of object data structures such as the WEKA Instance. It can be used for studying the aggregation and deposition of amyloid-β peptide in brain tissue of Alzheimer’s disease rodent models.
Provides image analysis tools for segmentation, classification, and downstream analysis of tumour section images. CRImage is a Bioconductor package that allows cellularity scoring of tumours which can then be applied to correct molecular assay data for varying cellularity. It also comes with an algorithm for copy-number data correction given single nucleotide polymorphism (SNP) microarray data and cellular content of the tumours estimated by the image analysis.
Provides assistance for the analysis of high-throughput microscopy-based screens. imageHTS main features are segmentation of cells, extraction of quantitative cell features, prediction of cell types and visualization of data through web interface. This software offers a standardized access to remote screen data to facilitate the dissemination of high-throughput microscopy-based screens.
Provides macros for ImageJ to automatically analyze the size and intensity of objects/regions in microscope images. imagej-interactive-thresholding is useful for the quantification of image data in cell biology and other areas of research. It can measure the fluorescence intensity within the segmented regions in a different image channel. This tool allows users to modify the automatically detected regions prior.
Aims to divide nuclei from fluorescence microscopy images. segmentation aims to sort each pixel of an image into either background, cell or boundary. This tool can be useful to predict outlines of nuclei only. It can serve to assess the model's performance and to determine segmentations for new images.
Assists in exploration of possible watershed segmentation. Interactive-H-Watershed is a plugin for the image analysis software ImageJ. It provides an interactive way to explore local minima (maxima) on the fly. This module is based on Watershed, a common tool to segment objects in an 2D and 3D images. The method permits to gradually flood the valleys starting from their lowest point.
Allows to visualize and present your images in several dimensions. The functionality of this imaging toolbox expands constantly with a wide range of different modules that are tailored to specific applications or microscope accessories. AxioVision offers countless functions for applications in the field of biological and medical routine research.
Assists users in stomata detection. Stomatameasurer is an application that uses TIFF fluorescence images of leaves. All analyses are realized in a single step, and the tool prints out some meta information on the files, including treatment, well coords, time, pixel info and stack. A function is included to always gets the stomata objects anyway on the picture.
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.
Contains functionalities for processing and analysis image data. GoFigure2 is a platform which allows users to visualize and navigate through 4D multichannels bio-images. Besides, it aims to provide an automatic segmentation of nuclei and cell membranes and to enable the way of extracting data from bio-images.
Allows segmentation of fine structures. ABSnake is a contour model, available as an ImageJ plugin, that mixes two classical approaches of deformable models: deformable curves and classical active contours. The plugin can enter invaginations because points are attracted towards locations with high gradient magnitude along a direction perpendicular to the contour. It can reproduce the classical behavior of snake with high values of regularization, and can also segment very thin and complex structures such as ones present in biological images.
Allows users to automatically segment and track cells in video sequences, plot their trajectories, and evaluate various cell parameters. The comparison with two other software packages showed that DYNAMIK compares favorably and that it, being a MATLAB implementation, offers many additional features, such as scalability and interactivity.
Focuses on combinatorial optimization via graph cuts for digital image analysis. GC is a library aiming to finds solution to energy minimization based discrete labeling problems such as image segmentation. The software provides access to several algorithms, such as maximum flow algorithms, Metric approximation, Multi-label discrete energy optimization, and Image segmentation.
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