Limits...
Neuromantic - from semi-manual to semi-automatic reconstruction of neuron morphology.

Myatt DR, Hadlington T, Ascoli GA, Nasuto SJ - Front Neuroinform (2012)

Bottom Line: The ability to create accurate geometric models of neuronal morphology is important for understanding the role of shape in information processing.This paper describes Neuromantic, an open source system for three dimensional digital tracing of neurites.Practical considerations for reducing the computational time and space requirements of the extended algorithm are also discussed.

View Article: PubMed Central - PubMed

Affiliation: School of Systems Engineering, University of Reading Reading, UK.

ABSTRACT
The ability to create accurate geometric models of neuronal morphology is important for understanding the role of shape in information processing. Despite a significant amount of research on automating neuron reconstructions from image stacks obtained via microscopy, in practice most data are still collected manually. This paper describes Neuromantic, an open source system for three dimensional digital tracing of neurites. Neuromantic reconstructions are comparable in quality to those of existing commercial and freeware systems while balancing speed and accuracy of manual reconstruction. The combination of semi-automatic tracing, intuitive editing, and ability of visualizing large image stacks on standard computing platforms provides a versatile tool that can help address the reconstructions availability bottleneck. Practical considerations for reducing the computational time and space requirements of the extended algorithm are also discussed.

No MeSH data available.


An illustration of how the routing algorithm is extended to 3D by adding nodes on 3 × 3 pixel neighborhoods for the slices directly above and below the specified node.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3305991&req=5

Figure 3: An illustration of how the routing algorithm is extended to 3D by adding nodes on 3 × 3 pixel neighborhoods for the slices directly above and below the specified node.

Mentions: Extending the Dijkstra algorithm from two to three dimensions is straightforward: instead of adding just the 8 pixel-neighborhood of a pixel A to the list when A is expanded, the 9 pixels on the slices directly above and below to the open list are also added, as demonstrated in Figure 3. Even without altering the cost function, the algorithm then tends to correctly follow between slices as more in focus dendrite will have a higher neuriteness score.


Neuromantic - from semi-manual to semi-automatic reconstruction of neuron morphology.

Myatt DR, Hadlington T, Ascoli GA, Nasuto SJ - Front Neuroinform (2012)

An illustration of how the routing algorithm is extended to 3D by adding nodes on 3 × 3 pixel neighborhoods for the slices directly above and below the specified node.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3305991&req=5

Figure 3: An illustration of how the routing algorithm is extended to 3D by adding nodes on 3 × 3 pixel neighborhoods for the slices directly above and below the specified node.
Mentions: Extending the Dijkstra algorithm from two to three dimensions is straightforward: instead of adding just the 8 pixel-neighborhood of a pixel A to the list when A is expanded, the 9 pixels on the slices directly above and below to the open list are also added, as demonstrated in Figure 3. Even without altering the cost function, the algorithm then tends to correctly follow between slices as more in focus dendrite will have a higher neuriteness score.

Bottom Line: The ability to create accurate geometric models of neuronal morphology is important for understanding the role of shape in information processing.This paper describes Neuromantic, an open source system for three dimensional digital tracing of neurites.Practical considerations for reducing the computational time and space requirements of the extended algorithm are also discussed.

View Article: PubMed Central - PubMed

Affiliation: School of Systems Engineering, University of Reading Reading, UK.

ABSTRACT
The ability to create accurate geometric models of neuronal morphology is important for understanding the role of shape in information processing. Despite a significant amount of research on automating neuron reconstructions from image stacks obtained via microscopy, in practice most data are still collected manually. This paper describes Neuromantic, an open source system for three dimensional digital tracing of neurites. Neuromantic reconstructions are comparable in quality to those of existing commercial and freeware systems while balancing speed and accuracy of manual reconstruction. The combination of semi-automatic tracing, intuitive editing, and ability of visualizing large image stacks on standard computing platforms provides a versatile tool that can help address the reconstructions availability bottleneck. Practical considerations for reducing the computational time and space requirements of the extended algorithm are also discussed.

No MeSH data available.