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For installation and usage instructions, please visit https://github.com/hzdr-MedImaging/LyROI

Please cite nnU-Net and the respective paper when using LyROI.

 

List of available models:


	LyROI_Orig.zip: regular U-Net
	LyROI_ResM.zip: residual encoder U-Net (medium)
	LyROI_ResL.zip: residual encoder U-Net (large)
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          <dc:relation>doi:10.14278/rodare.2026</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/pet-center</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
          <dc:rights>info:eu-repo/semantics/closedAccess</dc:rights>
          <dc:title>Data to NEP paper</dc:title>
          <dc:type>info:eu-repo/semantics/other</dc:type>
          <dc:type>dataset</dc:type>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:rodare.hzdr.de:4199</identifier>
        <datestamp>2026-01-07T15:21:39Z</datestamp>
        <setSpec>software</setSpec>
        <setSpec>user-health</setSpec>
        <setSpec>user-hzdr</setSpec>
        <setSpec>user-pet-center</setSpec>
        <setSpec>user-rodare</setSpec>
        <setSpec>user-zrt</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:creator>Maus, Jens</dc:creator>
          <dc:creator>Nitschke, Janina</dc:creator>
          <dc:creator>Nikulin, Pavel</dc:creator>
          <dc:creator>Hofheinz, Frank</dc:creator>
          <dc:creator>Barth, Mareike</dc:creator>
          <dc:creator>Lemm, Sandy</dc:creator>
          <dc:creator>Richter, Lena</dc:creator>
          <dc:creator>Pietzsch, Jens</dc:creator>
          <dc:creator>Braune, Anja</dc:creator>
          <dc:creator>Ullrich, Martin</dc:creator>
          <dc:date>2026-01-07</dc:date>
          <dc:description>Collection of neural network models for automatic image segmentation of microscopic tumor spheroids. Intended to be used with nnU-Net deep-learning framework. Trained and tested on a total of microscopic images of mouse pheochromocytoma (MPC) tumor cells.

In addition to the trained network model, a PyQt5-based graphical user interface tool is provided. This tool provides a complete pipeline for handling microscopic spheroid image data, running deep-learning–based delineation, and curating results for continuous model improvement.

For installation and usage instructions, please visit https://github.com/hzdr-MedImaging/pyMarAI

Please cite nnU-Net and the respective paper when using pyMarAI.

List of available model types:


	pyMarAI-1.0.0-ecat.zip: nnUNetv2 ready network (for ECAT7)
	pyMarAI-1.0.0-nifti.zip: nnUNetv2 ready network (for NIFTI)
</dc:description>
          <dc:identifier>https://rodare.hzdr.de/record/4199</dc:identifier>
          <dc:identifier>10.14278/rodare.4199</dc:identifier>
          <dc:identifier>oai:rodare.hzdr.de:4199</dc:identifier>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-42498</dc:relation>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-42497</dc:relation>
          <dc:relation>url:https://github.com/hzdr-MedImaging/pyMarAI</dc:relation>
          <dc:relation>doi:10.14278/rodare.4198</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/health</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/hzdr</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/pet-center</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/zrt</dc:relation>
          <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
          <dc:rights>https://creativecommons.org/licenses/by-sa/4.0/legalcode</dc:rights>
          <dc:subject>Tumor Spheroid Imaging</dc:subject>
          <dc:subject>Radiopharmacological Treatment Response Assays</dc:subject>
          <dc:subject>Delineation</dc:subject>
          <dc:subject>Cancer</dc:subject>
          <dc:subject>Deep-Learning</dc:subject>
          <dc:subject>Artifical Intelligence</dc:subject>
          <dc:subject>Convolutional Neural Networks</dc:subject>
          <dc:subject>Network model</dc:subject>
          <dc:title>pyMarAI: nnU-Net-based Tumor Spheroids Auto Delineation</dc:title>
          <dc:type>info:eu-repo/semantics/other</dc:type>
          <dc:type>software</dc:type>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:rodare.hzdr.de:4621</identifier>
        <datestamp>2026-04-20T18:10:40Z</datestamp>
        <setSpec>software</setSpec>
        <setSpec>user-health</setSpec>
        <setSpec>user-pet-center</setSpec>
        <setSpec>user-rodare</setSpec>
        <setSpec>user-zrt</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:creator>Nikulin, Pavel</dc:creator>
          <dc:creator>Hoberück, Sebastian</dc:creator>
          <dc:creator>Apostolova, Ivayla</dc:creator>
          <dc:creator>Maus, Jens</dc:creator>
          <dc:creator>Hüttmann, Andreas</dc:creator>
          <dc:creator>Dührsen, Ulrich</dc:creator>
          <dc:creator>Kroschinsky, Frank</dc:creator>
          <dc:creator>Kotzerke, Jörg</dc:creator>
          <dc:creator>von Bonin, Malte</dc:creator>
          <dc:creator>Bundschuh, Ralph</dc:creator>
          <dc:creator>Braune, Anja</dc:creator>
          <dc:creator>Hofheinz, Frank</dc:creator>
          <dc:date>2025-11-26</dc:date>
          <dc:description>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 [18F]FDG-PET/CT scans from 716 patients with Non-Hodgkin lymphoma participating in the PETAL trial.

For installation and usage instructions, please visit https://github.com/hzdr-MedImaging/LyROI

Please cite nnU-Net and the respective paper when using LyROI.

 

List of models:


	PET/CT:
	
		LyROI_Orig.zip: regular U-Net
		LyROI_ResM.zip: residual encoder U-Net (medium)
		LyROI_ResL.zip: residual encoder U-Net (large)
	
	
	PET-only:
	
		LyROI_PET_Orig.zip: regular U-Net
		LyROI_PET_ResM.zip: residual encoder U-Net (medium)
		LyROI_PET_ResL.zip: residual encoder U-Net (large)
	
	
</dc:description>
          <dc:identifier>https://rodare.hzdr.de/record/4621</dc:identifier>
          <dc:identifier>10.14278/rodare.4621</dc:identifier>
          <dc:identifier>oai:rodare.hzdr.de:4621</dc:identifier>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-42318</dc:relation>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-42236</dc:relation>
          <dc:relation>url:https://github.com/hzdr-MedImaging/LyROI</dc:relation>
          <dc:relation>doi:10.14278/rodare.4160</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/health</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/pet-center</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/zrt</dc:relation>
          <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
          <dc:rights>https://creativecommons.org/licenses/by-sa/4.0/legalcode</dc:rights>
          <dc:subject>FDG PET</dc:subject>
          <dc:subject>Total Metabolic Tumor Volume</dc:subject>
          <dc:subject>TMTV</dc:subject>
          <dc:subject>Non-Hodgkin Lymphoma</dc:subject>
          <dc:subject>Convolutional Neural Network</dc:subject>
          <dc:subject>Delineation</dc:subject>
          <dc:title>LyROI – nnU-Net-based Lymphoma Total Metabolic Tumor Volume Delineation</dc:title>
          <dc:type>info:eu-repo/semantics/other</dc:type>
          <dc:type>software</dc:type>
        </oai_dc:dc>
      </metadata>
    </record>
  </ListRecords>
</OAI-PMH>
