November 26, 2025 Software Open Access

Nikulin, Pavel; Hoberück, Sebastian; Apostolova, Ivayla; Maus, Jens; Hüttmann, Andreas; Dührsen, Ulrich; Kroschinsky, Frank; Kotzerke, Jörg; von Bonin, Malte; Bundschuh, Ralph; Braune, Anja; Hofheinz, Frank

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{
  "version": "1.0.1", 
  "issued": {
    "date-parts": [
      [
        2025, 
        11, 
        26
      ]
    ]
  }, 
  "type": "article", 
  "DOI": "10.14278/rodare.4177", 
  "id": "4177", 
  "author": [
    {
      "family": "Nikulin, Pavel"
    }, 
    {
      "family": "Hober\u00fcck, Sebastian"
    }, 
    {
      "family": "Apostolova, Ivayla"
    }, 
    {
      "family": "Maus, Jens"
    }, 
    {
      "family": "H\u00fcttmann, Andreas"
    }, 
    {
      "family": "D\u00fchrsen, Ulrich"
    }, 
    {
      "family": "Kroschinsky, Frank"
    }, 
    {
      "family": "Kotzerke, J\u00f6rg"
    }, 
    {
      "family": "von Bonin, Malte"
    }, 
    {
      "family": "Bundschuh, Ralph"
    }, 
    {
      "family": "Braune, Anja"
    }, 
    {
      "family": "Hofheinz, Frank"
    }
  ], 
  "title": "LyROI \u2013 nnU-Net-based Lymphoma Total Metabolic Tumor Volume Segmentation", 
  "publisher": "Rodare", 
  "abstract": "<p>Collection of neural network models for metabolic tumor volume segmentation in (Non-Hodgkin) lymphoma patients in FDG-PET/CT images. Intended to use within nnU-Net deep learning framework. Trained with a total of 1192 [<sup>18</sup>F]FDG-PET/CT scans from 716 patients with Non-Hodgkin&nbsp;lymphoma participating in the <a href=\"https://doi.org/10.1200/jco.2017.76.8093\">PETAL</a> trial.</p>\n\n<p>For installation and usage instructions, please visit <a href=\"http://github.com/hzdr-MedImaging/LyROI\">https://github.com/hzdr-MedImaging/LyROI</a></p>\n\n<p>Please cite&nbsp;<a href=\"https://www.nature.com/articles/s41592-020-01008-z\">nnU-Net</a>&nbsp;and the respective paper when using LyROI.</p>"
}