Artificial Intelligence-Based Organ Delineation for Radiation Treatment Planning of Prostate Cancer on Computed Tomography von Polymeri, Eirini, Johnsson, Åse A., Enqvist, Olof, Ulén, Johannes, Pettersson, Niclas, Nordström, Fredrik, Kindblom, Jon, Trägårdh, Elin, Edenbrandt, Lars, Kjölhede, Henrik

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Prognostic value of automatically acquired biomarkers using artificial intelligence in 18F-Choline PET/CT in high-risk prostate cancer von Borrelli, Pablo, Henrik, Kjalhede, Enqvist, Olof, Polymeri, Eirini, Ohlsson, Mattias, Edenbrandt, Lars

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Deep learning‐based quantification of PET/CT prostate gland uptake: association with overall survival von Polymeri, Eirini, Sadik, May, Kaboteh, Reza, Borrelli, Pablo, Enqvist, Olof, Ulén, Johannes, Ohlsson, Mattias, Trägårdh, Elin, Poulsen, Mads H., Simonsen, Jane A., Hoilund‐Carlsen, Poul Flemming, Johnsson, Åse A., Edenbrandt, Lars

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Automated quantification of reference levels in liver and mediastinal blood pool for the Deauville therapy response classification using FDG‐PET/CT in Hodgkin and non‐Hodgkin lymph... von Sadik, May, Lind, Erica, Polymeri, Eirini, Enqvist, Olof, Ulén, Johannes, Trägårdh, Elin

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Variability in reference levels for Deauville classifications applied to lymphoma patients examined with 18F-FDG-PET/CT von Sadik, May, Lind, Erica, Enqvist, Olof, Ulén, Johannes, Polymeri, Eirini, Trägårdh, Elin, Edenbrandt, Lars

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Automated quantification of reference levels in liver and mediastinum (blood pool) for the Deauville therapy response classification using FDG-PET/CT in lymphoma patients von Lind, Erica, Sadik, May, Enqvist, Olof, Ulén, Johannes, Polymeri, Eirini, Trägårdh, Elin, Edenbrandt, Lars

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Artificial intelligence-based measurements of PET/CT imaging biomarkers are associated with disease-specific survival of high-risk prostate cancer patients von Polymeri, Eirini, Kjölhede, Henrik, Enqvist, Olof, Ulén, Johannes, Poulsen, Mads H., Simonsen, Jane A., Borrelli, Pablo, Trägårdh, Elin, Johnsson, Åse A., Høilund-Carlsen, Poul Flemming, Edenbrandt, Lars

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Convolutional neural network based quantification of choline uptake in PET/CT studies is associated with overall survival in patients with prostate cancer von Kaboteh, Reza, Polymeri, Eirini, Sadik, May, Enqvist, Olof, Ulén, Johannes, Ohlsson, Mattias, Trägårdh, Elin, Poulsen, Mads, Simonsen, Jane Angel, Høilund-Carlsen, Poul Flemming, Johnsson, Åse, Edenbrandt, Lars

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Analytical validation of an automated method for segmentation of the prostate gland in CT images von Sadik, May, Polymeri, Eirini, Kaboteh, Reza, Enqvist, Olof, Ulén, Johannes, Trägårdh, Elin, Poulsen, Mads, Simonsen, Jane Angel, Høilund-Carlsen, Poul Flemming, Johnsson, Åse, Edenbrandt, Lars

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3D prostate gland uptake of 18F-choline - association with overall survival in patients with hormone-naïve prostate cancer von Sadik, May, Polymeri, Eirini, Kaboteh, Reza, Enqvist, Olof, Fejne, Frida, Kahl, Fredrik, Ohlsson, Mattias, Tragardh, Elin, Simonsen, Jane, Poulsen, Mads, Hoilund-Carlsen, Poul Flemming, Edenbrandt, Lars

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Automated 3D segmentation of the prostate gland in CT images - a first step towards objective measurements of prostate uptake in PET and SPECT images von Sadik, May, Polymeri, Eirini, Kaboteh, Reza, Enqvist, Olof, Fejne, Frida, Kahl, Fredrik, Tragardh, Elin, Poulsen, Mads, Simonsen, Jane, Hoilund-Carlsen, Poul Flemming, Johnsson, Ãse, Edenbrandt, Lars

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