ArticleNature communications2024
A modular framework for multi-scale tissue imaging and neuronal segmentation.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A Streamlined Workflow for Purkinje Cell Labeling and High-Resolution Analyses of Dendrites and Spines in Mice.eNeuro · 2026Article
- A workflow for semi-automated volume correlative light microscopy and transmission electron tomography.Journal of microscopy · 2025Article
- SpyDen: simplifying molecular and structural analysis across spines and dendrites.Bioinformatics (Oxford, England) · 2025Article
- Super-resolution microscopy and deep learning methods: what can they bring to neuroscience: from neuron to 3D spine segmentation.Frontiers in neuroinformatics · 2025Review
- A modular framework for multi-scale tissue imaging and neuronal segmentation.Nature communications · 2024Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The development of robust tools for segmenting cellular and sub-cellular neuronal structures lags behind the massive production of high-resolution 3D images of neurons in brain tissue. The challenges are principally related to high neuronal density and low signal-to-noise characteristics in thick samples, as well as the heterogeneity of data acquired with different imaging methods. To address this issue, we design a framework which includes sample preparation for high resolution imaging and image analysis. Specifically, we set up a method for labeling thick samples and develop SENPAI, a scalable algorithm for segmenting neurons at cellular and sub-cellular scales in conventional and super-resolution STimulated Emission Depletion (STED) microscopy images of brain tissues. Further, we propose a validation paradigm for testing segmentation performance when a manual ground-truth may not exhaustively describe neuronal arborization. We show that SENPAI provides accurate multi-scale segmentation, from entire neurons down to spines, outperforming state-of-the-art tools. The framework will empower image processing of complex neuronal circuitries.
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Registered trials
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