ArticleNature plants2023
Plantorganelle Hunter is an effective deep-learning-based method for plant organelle phenotyping in electron microscopy.
Article in Nature plants, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed, 14 citations in OpenAlex.
- Characterization of Viruses in Phloem by Correlative X-Ray Microtomography (μCT)-Volume Electron Microscopy (vEM) Imaging.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Nellie: automated organelle segmentation, tracking and hierarchical feature extraction in 2D/3D live-cell microscopy.Nature methods · 2025Article
- The Soil-Plant Continuity of Rare Earth Elements: Insights into an Enigmatic Class of Xenobiotics and Their Interactions with Plant Structures and Processes.Journal of xenobiotics · 2025Review
- The pipelines of deep learning-based plant image processing.Quantitative plant biology · 2025Review
- Letter to the Editor: Spatial proximity of tumor-immune interactions predicts patient outcome in hepatocellular carcinoma.Discover oncology · 2024Article
- Noninvasive Abiotic Stress Phenotyping of Vascular Plant in Each Vegetative Organ View.Plant phenomics (Washington, D.C.) · 2024Article
Corrections and comments
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Authors and funding
19 authors at 6 institutions in 4 countries.
Funding
Abstract
Accurate delineation of plant cell organelles from electron microscope images is essential for understanding subcellular behaviour and function. Here we develop a deep-learning pipeline, called the organelle segmentation network (OrgSegNet), for pixel-wise segmentation to identify chloroplasts, mitochondria, nuclei and vacuoles. OrgSegNet was evaluated on a large manually annotated dataset collected from 19 plant species and achieved state-of-the-art segmentation performance. We defined three digital traits (shape complexity, electron density and cross-sectional area) to track the quantitative features of individual organelles in 2D images and released an open-source web tool called Plantorganelle Hunter for quantitatively profiling subcellular morphology. In addition, the automatic segmentation method was successfully applied to a serial-sectioning scanning microscope technique to create a 3D cell model that offers unique views of the morphology and distribution of these organelles. The functionalities of Plantorganelle Hunter can be easily operated, which will increase efficiency and productivity for the plant science community, and enhance understanding of subcellular biology.
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Registered trials
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