Filament tracing

The ultimate goal of the NET framework is to make images of networks processable by computers. Therefore we want to have a pixel based image as input, as output we want a representation of the network visible in the image that retains as much information about the original network as possible. NET achives this by first segmenting the image and then vectorizing the network and then extracting information. The information we extract is

• First and foremost the graph of the network. We find the crossings (nodes) and connections between crossings (edges) and therefore extract information about the neighborhood relations, the topology of the network.
• We also extract the coordinates of all nodes which enables us to embed them into space. We therefore extract information about the geometry of the network.
• Last but not least we track the radii of the edges in the extraction process. Therefore every edge has a radius which can be identified with its conductivity.

In the following we will first provide detailed instructions on how to install NET on several platforms. Then we describe the functionality and options of each of the four scripts that make up the NET framework.

ORION: Online Reconstruction and functional Imaging Of Neurons: segmentation and tracing of neurons for reconstruction.

A project to develop tools that explore single neuron function via sophisticated image analysis. ORION software bridges advanced optical imaging and compartmental modeling of neuronal function by rapidly, accurately, and robustly generating, from structural image data, a cylindrical morphology model suitable for simulating neuronal function. The goal of this project is to develop a computational and experimental framework to allow real-time mapping of functional imaging data (e.g., spatio-temporal patterns of dendritic voltages or intracellularions) to neuronal structure, during the very limited duration of an acute experiment.

The invention comprises a software tool, NeuronMetrics, which functions as a set of modules that run in the open-source program ImageJ. NeuronMetrics features a novel method for estimating neural “branch number” (a measure of the axonal complexity) from two-dimensional images. In addition, the tool features a novel method for modeling neural structure in large “gaps” that result from image artifacts.

Neural Circuit Tracer (NCTracer) is open source software for automated and manual tracing of neurites from light microscopy stacks of images. NCTracer has more than one workflow available for neuron tracing. 

"The Neural Circuit Tracer is open source software built using Java (Sun Microsystems) and Matlab (MathWorks, Inc., Natick MA). It is based on the core of ImageJ (http://rsbweb.nih.gov/ij) and the graphic user interface has been developed by using Java Swings. The software combines anumber of functionalities of ImageJ with several newly developed functions for automated and manual tracing of neurites. The Neural Circuit Tracer is designed in a way
that will allow the users to add any plug-ins developed for ImageJ. More importantly, functions written in MatLab and converted into Java with Matlab JA toolbox can also be added to the Neural Circuit Tracer." 

AnaMorf is a plug-in developed for the ImageJ platform (rsb.info.nih.gov/ij) to analyse the microscopic morphology of filamentous microbes. The program returns average data on a population of mycelial elements, using the descriptors projected area, circularity, total hyphal length, number of hyphal tips, hyphal growth unit, lacunarity and fractal dimension. The plug-in accepts as input a user-specified directory of images, analysing each and outputing tabulated results.