The reconstruction of neuron morphology allows to investigate how the brain works, which is one of the foremost challenges in neuroscience. This process aims at extracting the neuronal structures from microscopic imaging data. The great advances in microscopic technologies have made a huge amount of data available at the micro-, or even lower, resolution where manual inspection is time consuming, prone to error and utterly impractical. This has motivated the development of methods to automatically trace the neuronal structures, a task also known as neuron tracing.
A tool for creating and analyzing realistic, meaningful, and quantifiable neuron reconstructions from microscope images. Perform detailed morphometric analysis of neurons, such as quantifying: 1) the number of dendrites, axons, nodes, synapses, and spines, 2) the length, width, and volume of dendrites and axons, 3) the area and volume of the soma and 4) the complexity and extension of neurons.
Handles tera-scale serial section electron microscopes (EM) image datasets for neural circuit rebuilding. TrakEM2 is a plugin that can be run through the ImageJ software. It includes multiple features allowing users to measure, visualize and annotate neuronal components. The application can be used for recording images from focused ion beam-scanning electron microscope (FIBSEM) or for reconstructing neuronal lineages and organs.
Traces and analyzes neurites in fluorescence microscopy images. NeuronJ consists in a semi-automatic neurite tracing technique that employs a global optimization algorithm and second-order image feature analysis, making it robust against noise, varying or discontinuous background intensities, and varying or locally diminishing neurite contrast. It can thus be applied to a wide range of images without changing its parameters.
Offers a platform for neurons rebuilding. NeuRA is able to handle image stacks from 2-photon microscopy and to perform their automatic conversion. The application includes a graphic interface allowing users to filter raw data for then segmenting it. Lastly, the software can reconstruct the geometry. It can be used for investigating neuronal plasticity.
An application for semi-automated tracing of neurons to quickly annotate noisy datasets and construct complex neuronal topologies. Simple Neurite Tracer is designed to allow easy semi-automatic tracing of neurons or other tube-like structures (e.g. blood vessels) through 3D image stacks. The plugin has built-in tools for analysis and hardware accelerated 3D visualization of the results. Data can be imported and exported in SWC files for interaction with other software, or details of the traces can be exported as CSV files for analysis in spreadsheets or statistical software. The native file format is open and XML-based.
Designed to extend any base neuron-tracing algorithm to be able to trace virtually unlimited data volumes. UltraTracer was applied to neuron-tracing algorithms with different design principles and tested on challenging human and mouse neuron datasets that have hundreds of billions of voxels. Results indicate that UltraTracer is scalable, accurate, and about 3 to 6 times more efficient compared to other state-of-the-art approaches.
Allows reconstruction of neuronal structures from confocal and multi-photon images. NeuronStudio provides tools for manual, semi-manual, and automatic tracing of the dendritic arbor as well as manual and automatic detection and classification of dendritic spines. In addition, advanced 2D and 3D visualization techniques facilitate the verification of the reconstruction, as well as allowing accurate manual editing.