ReviewBrain research reviews2011
Automated reconstruction of neuronal morphology: an overview.
Review in Brain research reviews, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.
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Who cites it
77 citing papers in PubMed.
- Automated Proofreading of Digitally Reconstructed Neural Morphology Enhances Accuracy, Scalability, and Standardization.bioRxiv : the preprint server for biology · 2026Article
- SPCNNet: spiking point cloud neural network for morphological neuron classification.Scientific reports · 2026Article
- Layer-specific input to medial prefrontal cortex is linked to stress susceptibility.Translational psychiatry · 2025Article
- High-throughput analysis of dendrite and axonal arbors reveals transcriptomic correlates of neuroanatomy.Nature communications · 2024Article
- Synthesis of geometrically realistic and watertight neuronal ultrastructure manifolds for in silico modeling.Briefings in bioinformatics · 2024Article
- Connecto-informatics at the mesoscale: current advances in image processing and analysis for mapping the brain connectivity.Brain informatics · 2024Review
- From pixels to connections: exploring in vitro neuron reconstruction software for network graph generation.Communications biology · 2024Review
- DNeuroMAT: A Deep-Learning-Based Neuron Morphology Analysis Toolbox.Methods in molecular biology (Clifton, N.J.) · 2024Article
- NeuroEditor: a tool to edit and visualize neuronal morphologies.Frontiers in neuroanatomy · 2024Article
- Online conversion of reconstructed neural morphologies into standardized SWC format.Nature communications · 2023Article
- RGC-Net: An Automatic Reconstruction and Quantification Algorithm for Retinal Ganglion Cells Based on Deep Learning.Translational vision science & technology · 2023Article
- Ultraliser: a framework for creating multiscale, high-fidelity and geometrically realistic 3D models for in silico neuroscience.Briefings in bioinformatics · 2023Article
- Neuron tracing from light microscopy images: automation, deep learning and bench testing.Bioinformatics (Oxford, England) · 2022Review
- Super-resolution Segmentation Network for Reconstruction of Packed Neurites.Neuroinformatics · 2022Article
- Smart imaging to empower brain-wide neuroscience at single-cell levels.Brain informatics · 2022Review
- Reconstruction of the Hippocampus.Advances in experimental medicine and biology · 2022Article
- Digital Reconstruction of the Neuro-Glia-Vascular Architecture.Cerebral cortex (New York, N.Y. : 1991) · 2021Article
- Optimization of Neurite Tracing and Further Characterization of Human Monocyte-Derived-Neuronal-like Cells.Brain sciences · 2021Article
- Comparing Automated Morphology Quantification Software on Dendrites of Uninjured and Injured Drosophila Neurons.Neuroinformatics · 2021Article
- Neuron tracing and quantitative analyses of dendritic architecture reveal symmetrical three-way-junctions and phenotypes of git-1 in C. elegans.PLoS computational biology · 2021Article
17 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors.
Funding
Abstract
Digital reconstruction of neuronal morphology is a powerful technique for investigating the nervous system. This process consists of tracing the axonal and dendritic arbors of neurons imaged by optical microscopy into a geometrical format suitable for quantitative analysis and computational modeling. Algorithmic automation of neuronal tracing promises to increase the speed, accuracy, and reproducibility of morphological reconstructions. Together with recent breakthroughs in cellular imaging and accelerating progress in optical microscopy, automated reconstruction of neuronal morphology will play a central role in the development of high throughput screening and the acquisition of connectomic data. Yet, despite continuous advances in image processing algorithms, to date manual tracing remains the overwhelming choice for digitizing neuronal morphology. We summarize the issues involved in automated reconstruction, overview the available techniques, and provide a realistic assessment of future perspectives.
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