{
  "abstract": "The International Mouse Phenotyping Consortium (IMPC) maintains a large archive of whole-body dorsoventral radiographs. However, heterogeneity in file formats, metadata completeness, orientation, and image quality limits its reuse for large-scale quantitative analysis. We present FERDINAND (Framework for Extracting and Restructuring Distributed IMPC radiographs into a Normalised, AI-ready Navigable Dataset), an open framework for programmatic access, harmonisation, quality control, and curation of IMPC radiographs. FERDINAND combines metadata retrieval and local radiograph archiving with centre-aware preprocessing, automated exposure screening, orientation standardisation, and clustering-assisted visual curation. Applied to IMPC Data Release 24, FERDINAND organises 104,819 radiographs acquired between February 2012 and June 2025 across ten phenotyping centres and 6,306 single-gene knockout mouse lines, with semi-automated curation recorded for every image. As an independent validation of the harmonised output, a DeepLabCut-based bone-morphometry pipeline showed that FERDINAND-processed radiographs improve data efficiency for landmark detection: at reduced training-set sizes, they achieve better performance than original radiographs and require fewer manual annotations to reach a given level of quality. FERDINAND provides a reproducible foundation for artificial intelligence (AI)-ready analysis and scalable quantitative phenotyping of heterogeneous IMPC and comparable radiograph resources. The complete FERDINAND source code is openly available on GitHub.",
  "abstract_shown": true,
  "affiliations": [
    "Helmholtz Zentrum München, German Research Center for Environmental Health"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "name": "R. Steinkamp"
    },
    {
      "name": "H. Maier"
    },
    {
      "name": "M. Hrabe de Angelis"
    },
    {
      "affs": [
        0
      ],
      "name": "E. Schneltzer"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cr74s3vank3b5.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.07.757287",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.07.757287v1.full",
  "id": "cr74s3vank3b5",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.07.757287v1",
  "language": null,
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioinformatics"
    ],
    [
      "openalex",
      "1710|Research Data Management Practices"
    ]
  ],
  "openalex": "W7222103821",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.07.757287v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-07",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/cr74s3vank3b5.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:27:53Z",
      "native_id": "10.64898/2026.10.07.757287",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.07.757287v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "FERDINAND: An Open Framework for Download and AI-ready Preprocessing of IMPC 2D Radiographs",
  "title_text": "FERDINAND: An Open Framework for Download and AI-ready Preprocessing of IMPC 2D Radiographs",
  "type": "preprint",
  "updated_at": "2026-10-30T12:27:53Z",
  "url": "https://research.draconitic.com/paper/cr74s3vank3b5",
  "venue": "bioRxiv",
  "versions": []
}