ArticleNature communications2019
Precise segmentation of densely interweaving neuron clusters using G-Cut.
Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Dendritome mapping reveals the spatial organization of striatal neuron morphology.Nature neuroscience · 2025Article
- Automatic and accurate reconstruction of long-range axonal projections of single-neuron in mouse brain.eLife · 2025Article
- A neuronal imaging dataset for deep learning in the reconstruction of single-neuron axons.Frontiers in neuroinformatics · 2025Article
- Super-resolution microscopy and deep learning methods: what can they bring to neuroscience: from neuron to 3D spine segmentation.Frontiers in neuroinformatics · 2025Review
- Neuronal diversity and stereotypy at multiple scales through whole brain morphometry.Nature communications · 2024Article
- Automated neuronal reconstruction with super-multicolour Tetbow labelling and threshold-based clustering of colour hues.Nature communications · 2024Article
- Connecto-informatics at the mesoscale: current advances in image processing and analysis for mapping the brain connectivity.Brain informatics · 2024Review
- A modular framework for multi-scale tissue imaging and neuronal segmentation.Nature communications · 2024Article
- Between neurons and networks: investigating mesoscale brain connectivity in neurological and psychiatric disorders.Frontiers in neuroscience · 2024Review
- Full-Spectrum Neuronal Diversity and Stereotypy through Whole Brain Morphometry.Research square · 2023Article
- BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets.Nature methods · 2023Article
- Tracing weak neuron fibers.Bioinformatics (Oxford, England) · 2023Article
- SNAP: a structure-based neuron morphology reconstruction automatic pruning pipeline.Frontiers in neuroinformatics · 2023Article
- nAdder: A scale-space approach for the 3D analysis of neuronal traces.PLoS computational biology · 2022Article
- Article
- Hidden Markov modeling for maximum probability neuron reconstruction.Communications biology · 2022Article
- Accelerating SSSP for Power-Law Graphs.FPGA. ACM International Symposium on Field-Programmable Gate Arrays · 2022Article
- Fluorescent transgenic mouse models for whole-brain imaging in health and disease.Frontiers in molecular neuroscience · 2022Review
- Prediction of RNA subcellular localization: Learning from heterogeneous data sources.iScience · 2021Review
- Quantification of relative neurite tortuosity using Fourier transforms.Journal of neuroscience methods · 2021Article
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Authors and funding
14 authors.
Funding
Abstract
Characterizing the precise three-dimensional morphology and anatomical context of neurons is crucial for neuronal cell type classification and circuitry mapping. Recent advances in tissue clearing techniques and microscopy make it possible to obtain image stacks of intact, interweaving neuron clusters in brain tissues. As most current 3D neuronal morphology reconstruction methods are only applicable to single neurons, it remains challenging to reconstruct these clusters digitally. To advance the state of the art beyond these challenges, we propose a fast and robust method named G-Cut that is able to automatically segment individual neurons from an interweaving neuron cluster. Across various densely interconnected neuron clusters, G-Cut achieves significantly higher accuracies than other state-of-the-art algorithms. G-Cut is intended as a robust component in a high throughput informatics pipeline for large-scale brain mapping projects.
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