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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{
  "@context": "https://schema.org/", 
  "version": "1.0.1", 
  "creator": [
    {
      "@type": "Person", 
      "affiliation": "Department of Positron Emission Tomography, Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany", 
      "@id": "https://orcid.org/0000-0002-4568-4018", 
      "name": "Nikulin, Pavel"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Department of Nuclear Medicine, University Hospital Carl Gustav Carus, Technische Universit\u00e4t Dresden, Dresden, Germany", 
      "name": "Hober\u00fcck, Sebastian"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Department for Diagnostic and Interventional Radiology and Nuclear Medicine, University Hospital Hamburg-Eppendorf, Hamburg, Germany", 
      "name": "Apostolova, Ivayla"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Department of Positron Emission Tomography, Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany", 
      "@id": "https://orcid.org/0000-0002-7195-9927", 
      "name": "Maus, Jens"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Department of Hematology, West German Cancer Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany", 
      "name": "H\u00fcttmann, Andreas"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Department of Hematology, West German Cancer Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany", 
      "name": "D\u00fchrsen, Ulrich"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Medical Department I, Dresden University Hospital, Dresden, Germany", 
      "name": "Kroschinsky, Frank"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Department of Nuclear Medicine, University Hospital Carl Gustav Carus, Technische Universit\u00e4t Dresden, Dresden, Germany", 
      "name": "Kotzerke, J\u00f6rg"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Medical Department I, Dresden University Hospital, Dresden, Germany", 
      "name": "von Bonin, Malte"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Department of Nuclear Medicine, University Hospital Carl Gustav Carus, Technische Universit\u00e4t Dresden, Dresden, Germany", 
      "name": "Bundschuh, Ralph"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Department of Positron Emission Tomography, Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany", 
      "@id": "https://orcid.org/0000-0001-7707-9413", 
      "name": "Braune, Anja"
    }, 
    {
      "@type": "Person", 
      "affiliation": "Department of Positron Emission Tomography, Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany", 
      "@id": "https://orcid.org/0000-0001-8016-4643", 
      "name": "Hofheinz, Frank"
    }
  ], 
  "url": "https://rodare.hzdr.de/record/4177", 
  "@id": "https://doi.org/10.14278/rodare.4177", 
  "description": "<p>Collection of neural network models for metabolic tumor volume delineation 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 <a href=\"https://link.springer.com/article/10.1007/s00259-026-07810-9\">respective paper</a> when using LyROI.</p>\n\n<p>&nbsp;</p>\n\n<p>List of available models:</p>\n\n<ul>\n\t<li><code>LyROI_Orig.zip</code>: regular U-Net</li>\n\t<li><code>LyROI_ResM.zip</code>: residual encoder U-Net (medium)</li>\n\t<li><code>LyROI_ResL.zip</code>: residual encoder U-Net (large)</li>\n</ul>", 
  "license": "https://creativecommons.org/licenses/by-sa/4.0/legalcode", 
  "sameAs": [
    "https://www.hzdr.de/publications/Publ-42318"
  ], 
  "codeRepository": "https://github.com/hzdr-MedImaging/LyROI", 
  "datePublished": "2025-11-26", 
  "name": "LyROI \u2013 nnU-Net-based Lymphoma Total Metabolic Tumor Volume Delineation", 
  "keywords": [
    "FDG PET", 
    "Total Metabolic Tumor Volume", 
    "TMTV", 
    "Non-Hodgkin Lymphoma", 
    "Convolutional Neural Network", 
    "Delineation"
  ], 
  "identifier": "https://doi.org/10.14278/rodare.4177", 
  "@type": "SoftwareSourceCode"
}