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Medical Physics|February 26, 2026
A prescription-free, radiobiology-based framework for automated VMAT planning: A feasibility study in primary prostate cancer radiotherapyDejan Kuhn, Simon K B Spohn, Constantinos Zamboglou, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|May 18, 2023
Investigation and benchmarking of U-Nets on prostate segmentation tasksShrajan Bhandary, Dejan Kuhn, Zahra Babaiee, et al.
European Radiology|April 25, 2024
Development and evaluation of two open-source nnU-Net models for automatic segmentation of lung tumors on PET and CT images with and without respiratory motion compensationMontserrat Carles, Dejan Kuhn, Tobias Fechter, et al.
Scientific Reports|October 30, 2024
A student trained convolutional neural network competing with a commercial AI software and experts in organ at risk segmentationSophia L Bürkle, Dejan Kuhn, Tobias Fechter, et al.
Radiation Oncology (London, England)|August 7, 2024
The impact of multicentric datasets for the automated tumor delineation in primary prostate cancer using convolutional neural networks on <sup>18</sup>F-PSMA-1007 PETJulius C Holzschuh, Michael Mix, Martin T Freitag, et al.
Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology|July 2, 2023
Deep learning based automated delineation of the intraprostatic gross tumour volume in PSMA-PET for patients with primary prostate cancerJulius C Holzschuh, Michael Mix, Juri Ruf, et al.
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