ArticleThe Journal of cell biology2023
ILEE: Algorithms and toolbox for unguided and accurate quantitative analysis of cytoskeletal images.
Article in The Journal of cell biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 17 citations in OpenAlex.
- A novel attention mechanism for noise-adaptive and robust segmentation of microtubules in microscopy images.BMC bioinformatics · 2026Article
- Independent roles of Arp2/3 complex and RIC4 protein in the control of epidermal cell shape.Planta · 2026Article
- From Pixels to Patterns: A Multidimensional Framework to Decode Cytoskeletal Organization.Computational and structural biotechnology journal · 2026Review
- From cells to pixels: A decision tree for designing bioimage analysis pipelines.Journal of microscopy · 2025Article
- Deep learning-based cytoskeleton segmentation for accurate high-throughput measurement of cytoskeleton density.Protoplasma · 2025Article
- Cecelia: a multifunctional image analysis toolbox for decoding spatial cellular interactions and behaviour.Nature communications · 2025Article
- Super-resolution microscopy and deep learning methods: what can they bring to neuroscience: from neuron to 3D spine segmentation.Frontiers in neuroinformatics · 2025Review
- Evaluation of image analysis tools for the measurement of cellular morphology.Frontiers in cell and developmental biology · 2025Review
- Morphometric analysis of actin networks.Molecular biology of the cell · 2024Article
- Microtubule Regulation in Plants: From Morphological Development to Stress Adaptation.Biomolecules · 2023Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
The eukaryotic cytoskeleton plays essential roles in cell signaling and trafficking, broadly associated with immunity and diseases in humans and plants. To date, most studies describing cytoskeleton dynamics and function rely on qualitative/quantitative analyses of cytoskeletal images. While state-of-the-art, these approaches face general challenges: the diversity among filaments causes considerable inaccuracy, and the widely adopted image projection leads to bias and information loss. To solve these issues, we developed the Implicit Laplacian of Enhanced Edge (ILEE), an unguided, high-performance approach for 2D/3D-based quantification of cytoskeletal status and organization. Using ILEE, we constructed a Python library to enable automated cytoskeletal image analysis, providing biologically interpretable indices measuring the density, bundling, segmentation, branching, and directionality of the cytoskeleton. Our data demonstrated that ILEE resolves the defects of traditional approaches, enables the detection of novel cytoskeletal features, and yields data with superior accuracy, stability, and robustness. The ILEE toolbox is available for public use through PyPI and Google Colab.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.