{
  "abstract": "Accurate image annotation is essential for training artificial intelligence (AI) systems in biomedical image analysis, enabling tasks such as cell detection, tissue quantification, and disease characterization. However, creating pixel-level annotations is a time-consuming and labor-intensive process that requires expert input, limiting the development and adoption of AI methods. Recent advances in foundation models, such as the Segment Anything Model (SAM), enable interactive object segmentation from simple user prompts, but their integration into widely used bioimage analysis platforms remains limited and often requires technical expertise. Here we show that SAMJ, a user-friendly plugin for ImageJ/Fiji, enables fast, interactive, and accurate image annotation on standard computers without requiring programming skills or specialized hardware. SAMJ integrates efficient SAM variants into a familiar graphical interface, allowing users to delineate objects in large scientific images in real time using simple clicks or bounding boxes. This approach significantly reduces annotation effort, accelerates dataset creation, and broadens access to advanced AI-assisted annotation tools for the biomedical research community.",
  "abstract_shown": true,
  "affiliations": [
    "Bioimage Analysis Unit, Institut Pasteur, Université Paris Cité, Paris, France",
    "Neuroscience and Life Sciences Department, Universidad Carlos III de Madrid, Getafe, Spain",
    "BioVisionCenter, University of Zurich, Zurich, Switzerland",
    "Bioengineering Department, Universidad Carlos III de Madrid, Leganes, Spain",
    "Center for Quantitative Cell Imaging, University of Wisconsin, Madison, USA",
    "Department of Mathematics and Computer Science, University of La Rioja, Logroño, Spain",
    "Central European Institute of Technology (CEITEC), Masaryk University, Brno, Czech Republic",
    "Centre for Biomedical Image Analysis, Masaryk University, Brno, Czech Republic",
    "Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK",
    "Donostia International Physics Center (DIPC), San Sebastian, Spain",
    "MRC Laboratory of Molecular Biology, Cambridge, UK",
    "CNRS UMR 3691, Institut Pasteur, Paris, France",
    "Faculty of Health Sciences, Universidad Carlos III de Madrid, Getafe, Spain",
    "Image Analysis Hub, Institut Pasteur, Université Paris Cité, Paris, France",
    "Biomedical Imaging Group and Center for Imaging, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. daniel.sage@epfl.ch",
    "Bioengineering Division, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain. mamunozb@ing.uc3m.es",
    "Neuroscience and Life Sciences Department, Universidad Carlos III de Madrid, Getafe, Spain. mamunozb@ing.uc3m.es"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 12,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Carlos García-López-de-Haro",
      "orcid": "0000-0003-4070-7097"
    },
    {
      "affs": [
        2,
        3
      ],
      "name": "Caterina Fuster-Barceló",
      "orcid": "0000-0002-4784-6957"
    },
    {
      "affs": [
        4
      ],
      "name": "Curtis Rueden",
      "orcid": "0000-0001-7055-6707"
    },
    {
      "affs": [
        5
      ],
      "name": "Jónathan Heras",
      "orcid": "0000-0003-4775-1306"
    },
    {
      "affs": [
        6,
        7
      ],
      "name": "Vladimír Ulman",
      "orcid": "0000-0002-4270-7982"
    },
    {
      "affs": [
        8,
        9,
        10
      ],
      "name": "Daniel Franco-Barranco",
      "orcid": "0000-0002-1109-110X"
    },
    {
      "affs": [
        5
      ],
      "name": "Adrián Inés",
      "orcid": "0000-0002-6989-1636"
    },
    {
      "affs": [
        4
      ],
      "name": "Kevin W. Eliceiri",
      "orcid": "0000-0001-8678-670X"
    },
    {
      "affs": [
        0,
        11,
        12
      ],
      "name": "Jean‐Christophe Olivo‐Marín",
      "orcid": "0000-0001-6796-0696"
    },
    {
      "affs": [
        13
      ],
      "name": "Jean-Yves Tinévez",
      "orcid": "0000-0002-0998-4718"
    },
    {
      "affs": [
        14
      ],
      "name": "Daniel Sage",
      "orcid": "0000-0002-1150-1623"
    },
    {
      "affs": [
        15,
        16
      ],
      "name": "Arrate Muñoz‐Barrutia",
      "orcid": "0000-0002-1573-1661"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/78km48sr4813p.bib",
  "cited_by": 9,
  "doi": "10.1038/s41467-026-71752-x",
  "fulltext_url": null,
  "id": "78km48sr4813p",
  "issns": [
    "2041-1723"
  ],
  "landing_url": "https://doi.org/10.1038/s41467-026-71752-x",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1304|Cell Image Analysis Techniques"
    ]
  ],
  "openalex": "W4415134882",
  "pdf_url": "https://www.nature.com/articles/s41467-026-71752-x.pdf",
  "pmcid": "PMC13279790",
  "pmid": "42315510",
  "published": "2026-06-18",
  "publisher": "Nature Portfolio",
  "ris": "https://research.draconitic.com/paper/78km48sr4813p.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:26:48Z",
      "native_id": "W4415134882",
      "source": "openalex",
      "url": "https://doi.org/10.1038/s41467-026-71752-x"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1304|Cell Image Analysis Techniques",
      "subfield": "biophysics"
    }
  ],
  "title": "SAMJ: fast image annotation on ImageJ/Fiji via segment anything model",
  "title_text": "SAMJ: fast image annotation on ImageJ/Fiji via segment anything model",
  "type": "peer-reviewed",
  "updated_at": "2026-11-05T13:20:47Z",
  "url": "https://research.draconitic.com/paper/78km48sr4813p",
  "venue": "Nature Communications",
  "versions": []
}