Cell motility is a critical part of many important biological processes. Automated and sensitive cell tracking is essential to cell motility studies where the tracking results can be used for diagnostic or curative decisions and where mathematical models can be developed to deepen our understanding of the mechanisms underlying cell motility.
Provides all the tools you need to visualize, analyze and validate 3D fluorescence images from a wide range of confocal microscopy, widefield and high content screening systems and is fully integrated for a seamless user experience. Get a full picture of the biological process with rapid, interactive, high-resolution volume rendering of time resolved, multichannel 3D data sets using Volocity software.
It is the ideal "glue" for easily integrating dissimilar fluorescent microscope hardware and peripherals into a single custom workstation, while providing all the tools needed to perform meaningful analysis of acquired images. The software offers many user-friendly application modules for biology-specific analysis such as cell signaling, cell counting, and protein expression.
Restores images from microscopic data. Huygens is based on the deconvolution approach that reassigns out-of-focus light to its origin, thus improves signal-to-noise in images. It can use physically-acquired or simulated point-spread functions (PSFs) for characterization of optical system being deconvolved. The tool shows high-performance in in-house tests on deconvolution compared to other software packages. It provides intuitive wizards for parameter selection and processing.
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.
Tracks intra- and inter-cellular phenomena. TrackMate simplifies the export and exchange of data and results with other tracking tools and/or analysis applications. It is useful for a wide range of tracking applications, ranging from single-particle tracking of subcellular organelles to cell lineage analysis. This tool can detect foci beyond what the human eye can distinguish via the quality threshold parameter.
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.
It is based on the MultiTracker plugin by Jeffrey Kuhn which is based on the Object tracker plugin by Wayne Rasband. In contrast to the Multitracker plugin, the number of objects may vary between successive frames (objects may appear or disappear). Mtrack2 will identify the objects in each frame, and then determine which objects in successive frames are closest together. If these are within a user-defined distance (the maximum velocity of the objects) they are assembled into tracks. When multiple objects are within the distance determined by the maximum velocity, the closest object is selected and the object is flagged in the output.