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LyROI – nnU-Net-based Lymphoma Total Metabolic Tumor Volume Segmentation

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

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 [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.

Files (8.8 GB)
Name Size
LyROI_Orig.zip
md5:af57366f934b5ddee335c7e41890b5e3
1.1 GB Download
LyROI_ResL.zip
md5:1bac0c45826c054d691ae7ee309cdb4a
3.8 GB Download
LyROI_ResM.zip
md5:a726321d41d2e835d781cb438b29edab
3.8 GB Download
VERSION
md5:3f74232ce9a4216c59b81b3d5aab57af
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