ArticleFrontiers in neuroinformatics2012
Neuromantic - from semi-manual to semi-automatic reconstruction of neuron morphology.
Article in Frontiers in neuroinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers.
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86 citing papers in PubMed.
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- A combinatory genetic strategy for targeting neurogliaform neurons in the mouse basolateral amygdala.Frontiers in cellular neuroscience · 2024Article
- The spike-timing-dependent plasticity of VIP interneurons in motor cortex.Frontiers in cellular neuroscience · 2024Article
- The short-term plasticity of VIP interneurons in motor cortex.Frontiers in synaptic neuroscience · 2024Article
- Structural and functional specializations of human fast-spiking neurons support fast cortical signaling.Science advances · 2023Article
- CellRemorph: A Toolkit for Transforming, Selecting, and Slicing 3D Cell Structures on the Road to Morphologically Detailed Astrocyte Simulations.Neuroinformatics · 2023Article
- The developmental profile of visual cortex astrocytes.iScience · 2023Article
- Cell-autonomous and differential endocannabinoid signaling impacts the development of presynaptic retinal ganglion cell axon connectivityFrontiers in synaptic neuroscience · 2023Article
- Retinal horizontal cells use different synaptic sites for global feedforward and local feedback signaling.Current biology : CB · 2022Article
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- Comparing Automated Morphology Quantification Software on Dendrites of Uninjured and Injured Drosophila Neurons.Neuroinformatics · 2021Article
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26 more citing papers are in PubMed but not listed here.
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4 authors.
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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.
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