neuron

Vaa3D is a handy, fast, and versatile 3D/4D/5D Image Visualization and Analysis System for Bioimages and Surface Objects. It also provides many unique functions that you may not find in other software. It is Open Source, and supports a very simple and powerful plugin interface and thus can be extended and enhanced easily.

Vaa3D is cross-platform (Mac, Linux, and Windows). This software suite is powerful for visualizing large- or massive-scale (giga-voxels and even tera-voxels) 3D image stacks and various surface data. Vaa3D is also a container of powerful modules for 3D image analysis (cell segmentation, neuron tracing, brain registration, annotation, quantitative measurement and statistics, etc) and data management. This makes Vaa3D suitable for various bioimage informatics applications, and a nice platform to develop new 3D image analysis algorithms for high-throughput processing. In short, Vaa3D streamlines the workflow of visualization-assisted analysis.

Vaa3D can render 5D (spatial-temporal) data directly in 3D volume-rendering mode; it supports convenient and interactive local and global 3D views at different scales... it comes with a number of plugins and toolboxes. Importantly, you can now write your own plugins to take advantage of the Vaa3D platform, possibly within minutes!

This software is designed for the rapid semi-automatic detection and quantification of synaptic protein puncta from 2D immunofluorescence images generated by confocal laser scanning microscopy.

neuTube is a collection of neuron reconstruction tools from fluorescence microscope images. It has an interactive system with a 3D viewer, which can be clicked in 3D and perform neuron tracing automatically and semi-automatically. It can automatically recognize branching points as junctions. Traced neurons can be exported to swc format, which could be imported by various software packages. neuTube has Win and Mac OS standalone executable builds and may also be installed by manual compilation. In addition, neuTube can be used as a plugin in Vaa3D.

**Collaborative Annotation Toolkit for Massive Amounts of Image Data** CATMAID is a Collaborative Annotation Toolkit for Massive Amounts of Image Data. It is designed to navigate, share and collaboratively annotate massive image data sets of biological specimens. The interface is inspired by GoogleMaps, with which it shares basic navigation concepts, enhanced to allow the exploration of 3D biological image data acquired by optical or physical sectioning microscopy techniques. The interface enables seamless sharing of regions of interest through bookmarks and synchronized navigation through multiple registered data sets. With massive biological image data sets it is unrealistic to create a sustainable centralized repository. A unique feature of CATMAID is its partially decentralized architecture where the presented image data can reside on any Internet accessible server and yet can be easily cross-referenced in the central database. In this way no image data are duplicated and the data producers retain full control over their images. CATMAID is intended to serve as data sharing platform for biologists using high-resolution imaging techniques to probe large specimens. Any high-throughput, high-content imaging project such as gene expression pattern screens would benefit from the interface for data sharing and annotation.

Neuron studio is a software package to reconstruct neurons from 3D confocal images. Reconstruction can be done manually, semi-manually or fully automatic. The images as well as the detected objects are rendered in 3D. A spine detection and classification function is also included. Results can be exported as a text file with coords of the spines. It seems that active development has stopped in 2009. NeuronStudio is being developed at the Computational Neurobiology and Imaging Center (CNIC), a research laboratory at the Neuroscience Department of the Mount Sinai School of Medicine in New York.

NeuronStudio can be used with default parameters or user-defined parameters (Fully or semi-automated).