Identifies cells of interest on imaging of large cell numbers in quantitative microscopy. Micropilot can automatically process complex fluorescence microscopy-based imaging assays. Users can train the software to detect objects in a fast low-resolution prescanning mode. This software is able to execute more complex imaging assays on selected object positions by following an online reconfiguration of the microscope system.
Allows quantification of clathrin-coated pit dynamics from fluorescence time-lapse data. cmeAnalysis provides functionalities including: (1) sensitive detection, (2) tracking (based on u-track), (3) master/slave detection for multi-channel data, (4) intensity-based classification of coated structures, and (5) lifetime analysis. It also contains a graphical user interface (GUI) for inspection of analysis results from individual movies.
Detects patch-based carcinoma in confocal laser endomicroscopy (CLE) images. This patch probability fusion method that can provide additional real-time information about the suspicious lesion, supportive to the clinical examination. The software can serve as an additional tool supporting the biopsy and the following histopathological examination. It was applied on CLE images of oral squamous cell carcinoma (OSCC).
Supports local analysis and is able to split a single trajectory into segments with different motion types. TraJClassifier is a Fiji plugin providing a practical and device-independent method to classify and segment particle trajectories into four main motion types. It loads trajectories from TrackMate (exported via the action "Export trajectories"), characterizes them using TraJ and classifies them into normal diffusion, subdiffusion, confined diffusion and directed/active motion by a random forest approach (through Renjin).
It is able to apply pattern recognition algorithms to two- and three-dimensional biological image sets as well as regions of interest (ROIs) in individual images for automatic classification and annotation. The customizability of BIOCAT is expected to be useful for providing effective and efficient solutions for a variety of biological problems involving image classification and annotation.
Provides a method for the segmentation and classification of 3D datasets in biological development. Generic 3D segmentation and classification in biological development is a software that builds his nuclei segmentation approach by learning from samples supplied by the user for the existing objects in image. This ImageJ plugin is based on the adaptive generic iterative thresholding algorithm (AGITA).
A user-friendly image-based classification algorithm inspired by WND-CHARM in (i) its ability to capture a wide variety of morphological aspects of the image, and (ii) the absence of requirement for segmentation. In order to make such an image-based classification method easily accessible to the biological research community, CP-CHARM relies on the widely-used open-source image analysis software CellProfiler for feature extraction.
Assists users to analyze three-dimensional microglia morphology in mammalian brains. MIC-MAC is a program that enables automatic 3D-morphology characterization and classification of thousands of individual microglia. This tool can capture morphological heterogeneity of microglia in large brain sections immunostained for cell-type specific morphological markers. Moreover, it permits: (1) semi-automated and reliable segmentation of all marker-positive cells within the volume, (2) automated extraction of geometrical and graph-based features for each reconstructed cell, or (3) filtering of artefactual structures.
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.
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.
0 - 0 of 0