Added Value of [18F]PSMA‐1007 PET/CT and PET/MRI in Patients With Biochemically Recurrent Prostate Cancer: Impact on Detection Rates and Clinical Management von Abrahamsen, Bendik S., Tandstad, Torgrim, Aksnessæther, Bjørg Y., Bogsrud, Trond V., Castillejo, Miguel, Hernes, Eivor, Johansen, Håkon, Keil, Thomas M. I., Knudtsen, Ingerid S., Langørgen, Sverre, Selnæs, Kirsten M., Bathen, Tone F., Elschot, Mattijs

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Radiation effects on crystalline L-asparagine, revisited: Radical formation by EMR and periodic DFT after X-irradiation at 275 K von Knudtsen, Ingerid S, Aalbergsjo, Siv G, Hole, Eli O, Sagstuen, Einar

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Direct Radiation Effects to the Amino Acid Side Chain: EMR and Periodic DFT of X‑Irradiated l‑Asparagine at 6 K von Øyen, Live F, Aalbergsjø, Siv G, Knudtsen, Ingerid S, Hole, Eli O, Sagstuen, Einar

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1099: Salvage radiotherapy of recurrent prostate cancer after PSMA PET/MRI and PET/CT von Knudtsen, Ingerid S., Abrahamsen, Bendik S., Selnæs, Kirsten M., Langørgen, Sverre, Keil, Thomas M., Johansen, Håkon, Castillejo, Miguel J., Bogsrud, Trond V., Aarsæther, Erling J., Haugnes, Hege S., Tandstad, Torgrim, Elschot, Mattijs, Bathen, Tone F.

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Radiation effects on crystalline l-asparagine, revisited: Radical formation by EMR and periodic DFT after X-irradiation at 275K von Knudtsen, Ingerid S., Aalbergsjø, Siv G., Hole, Eli O., Sagstuen, Einar

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A comparison of methods for fully automatic segmentation of tumors and involved nodes in PET/CT of head and neck cancers von Groendahl, Aurora Rosvoll, Skjei Knudtsen, Ingerid, Huynh, Bao Ngoc, Mulstad, Martine, Moe, Yngve Mardal, Knuth, Franziska, Tomic, Oliver, Indahl, Ulf Geir, Torheim, Turid, Dale, Einar, Malinen, Eirik, Futsaether, Cecilia Marie

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Pelvic PET/MR attenuation correction in the image space using deep learning von Abrahamsen, Bendik Skarre, Knudtsen, Ingerid Skjei, Eikenes, Live, Bathen, Tone Frost, Elschot, Mattijs

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Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics von Huynh, Bao Ngoc, Groendahl, Aurora Rosvoll, Tomic, Oliver, Liland, Kristian Hovde, Knudtsen, Ingerid Skjei, Hoebers, Frank, van Elmpt, Wouter, Malinen, Eirik, Dale, Einar, Futsaether, Cecilia Marie

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966: Uncertainty in deep learning-based automatic segmentations of head and neck cancer tumors von Huynh, Bao Ngoc, Groendahl, Aurora Rosvoll, Tomic, Oliver, Knudtsen, Ingerid Skjei, Hoebers, Frank, van Elmpt, Wouter, Dale, Einar, Malinen, Eirik, Futsaether, Cecilia Marie

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Positron emission tomography guided dose painting by numbers of lung cancer: Alanine dosimetry in an anthropomorphic phantom von Papoutsis, Iosif, Skjei Knudtsen, Ingerid, Peter Skaug Sande, Erlend, Louni Rekstad, Bernt, Öllers, Michel, van Elmpt, Wouter, Røthe Arnesen, Marius, Malinen, Eirik

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Corrigendum: Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics von Huynh, Bao Ngoc, Groendahl, Aurora Rosvoll, Tomic, Oliver, Liland, Kristian Hovde, Knudtsen, Ingerid Skjei, Hoebers, Frank, van Elmpt, Wouter, Malinen, Eirik, Dale, Einar, Futsaether, Cecilia Marie

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Impact of PET reconstruction algorithm and threshold on dose painting of non-small cell lung cancer von Knudtsen, Ingerid Skjei, van Elmpt, Wouter, Öllers, Michel, Malinen, Eirik

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Deep learning with uncertainty estimation for automatic tumor segmentation in PET/CT of head and neck cancers: impact of model complexity, image processing and augmentation von Huynh, Bao Ngoc, Groendahl, Aurora Rosvoll, Tomic, Oliver, Liland, Kristian Hovde, Knudtsen, Ingerid Skjei, Hoebers, Frank, van Elmpt, Wouter, Dale, Einar, Malinen, Eirik, Futsaether, Cecilia Marie

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A new method to assess pulmonary changes using 18 F-fluoro-2-deoxyglucose positron emission tomography for lung cancer patients following radiotherapy von Abravan, Azadeh, Knudtsen, Ingerid Skjei, Eide, Hanne Astrid, Løndalen, Ayca Muftuler, Helland, Åslaug, van Luijk, Peter, Malinen, Eirik

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Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics von Huynh, Bao Ngoc, Grøndahl, Aurora Rosvoll, Tomic, Oliver, Liland, Kristian Hovde, Knudtsen, Ingerid Søberg Skjei, Hoebers, Frank, van Elmpt, Wouter, Malinen, Eirik, Dale, Einar, Futsæther, Cecilia Marie

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Assessment of pulmonary 18F-FDG-PET uptake and cytokine profiles in non-small cell lung cancer patients treated with radiotherapy and erlotinib von Abravan, Azadeh, Eide, Hanne Astrid, Knudtsen, Ingerid Skjei, Løndalen, Ayca Muftuler, Helland, Åslaug, Malinen, Eirik

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Serum cytokine profiles and metabolic tumor burden in patients with non-small cell lung cancer undergoing palliative thoracic radiation therapy von Eide, Hanne A., MD, Knudtsen, Ingerid Skjei, MSc, Sandhu, Vandana, PhD, Løndalen, Ayca M., MD, Halvorsen, Ann Rita, MSc, Abravan, Azadeh, MSc, Kure, Elin H., PhD, Bogsrud, Trond V., MD, PhD, Brustugun, Odd Terje, MD, PhD, Kyte, Jon Amund, MD, PhD, Malinen, Eirik, PhD, Helland, Åslaug, MD, PhD

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Dose painting by numbers in a standard treatment planning system using inverted dose prescription maps von Arnesen, Marius Røthe, Knudtsen, Ingerid Skjei, Rekstad, Bernt Louni, Eilertsen, Karsten, Dale, Einar, Bruheim, Kjersti, Helland, Åslaug, Løndalen, Ayca Muftuler, Hellebust, Taran Paulsen, Malinen, Eirik

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Validation of dose painting of lung tumours using alanine/EPR dosimetry von Knudtsen, Ingerid Skjei, Svestad, Jørund Graadal, Skaug Sande, Erlend Peter, Rekstad, Bernt Louni, Rødal, Jan, van Elmpt, Wouter, Öllers, Michel, Hole, Eli Olaug, Malinen, Eirik

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A comparison of fully automatic segmentation of tumors and involved nodes in PET/CT of head and neck cancers von Groendahl, Aurora Rosvoll, Skjei Knudtsen, Ingerid, Huynh, Bao Ngoc, Mulstad, Martine, Moe, Yngve Mardal Mardal, Knuth, Franziska, Tomic, Oliver, Indahl, Ulf Geir, Torheim, Turid, Dale, Einar, Malinen, Eirik, Futsaether, Cecilia Marie

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