Neuronal tracing

Many image analysis based methods have been proposed to trace neuron morphology, usually in 3D, manually, semi-automatically or completely automatically.

The first computer-assisted neuron reconstruction system, now known as Neurolucida, was developed by Dr. Edmund Glaser and Dr. Hendrik Van der Loos in the 1960s.

Automated reconstructions of neurons can be done using model (e.g. spheres or tubes) fitting and marching,[7] pruning of over-reconstruction,[8] minimal cost connection of key points, ray-bursting and many others.

[9] Skeletonization is a critical step in automated neuron reconstruction, but in the case of all-path-pruning and its variants[10] it is combined with estimation of model parameters (e.g. tube diameters).

The major limitation of automated tracing is the lack of precision especially when the neuron morphology is complicated or the image has substantial amount of noise.

Semi-automated tracing is often thought to be a balanced solution that has acceptable time cost and reasonably good reconstruction accuracy.

The open source software Vaa3D-Neuron, Neurolucida 360, Imaris Filament Tracer and Aivia all provide both categories of methods.

Crowdsourcing is an alternative way to effectively collect collaborative manual reconstruction results for such image data sets.

A widely used database is http://NeuroMorpho.Org [23] which contains over 86,000 neuron morphology of >40 species contributed worldwide by a number of research labs.