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Olof Enqvist

Showing results (31-40 of 50) with videos related to

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Scientific Reports|December 14, 2021
Artificial intelligence based automatic quantification of epicardial adipose tissue suitable for large scale population studiesDavid Molnar, Olof Enqvist, Johannes Ulén, et al.
EJNMMI Research|February 27, 2026
Automated RECOMIA AI-based total metabolic tumor volume in lymphoma - a retrospective studyMay Sadik, Johanna Mörk, Jesus Lopez Urdaneta, et al.
Advances in Radiation Oncology|March 18, 2024
Artificial Intelligence-Based Organ Delineation for Radiation Treatment Planning of Prostate Cancer on Computed TomographyEirini Polymeri, Åse A Johnsson, Olof Enqvist, et al.
BMC Medical Imaging|September 17, 2025
Inter-reader agreement of quantitative FDG PET/CT biomarkers in lymphoma: a multicentre evaluation of MTV, TLG and DmaxElin Trägårdh, Malin Lewold, Jesus Lopez Urdaneta, et al.
Clinical Physiology and Functional Imaging|March 23, 2022
PET/CT imaging of spinal inflammation and microcalcification in patients with low back pain: A pilot study on the quantification by artificial intelligence-based segmentationReza Piri, Amalie H Nøddeskou-Fink, Oke Gerke, et al.
Diagnostics (Basel, Switzerland)|September 23, 2022
Freely Available, Fully Automated AI-Based Analysis of Primary Tumour and Metastases of Prostate Cancer in Whole-Body [<sup>18</sup>F]-PSMA-1007 PET-CTElin Trägårdh, Olof Enqvist, Johannes Ulén, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|August 13, 2021
"Global" cardiac atherosclerotic burden assessed by artificial intelligence-based versus manual segmentation in <sup>18</sup>F-sodium fluoride PET/CT scans: Head-to-head comparisonReza Piri, Lars Edenbrandt, Måns Larsson, et al.
European Journal of Radiology|April 1, 2019
Deep learning for segmentation of 49 selected bones in CT scans: First step in automated PET/CT-based 3D quantification of skeletal metastasesSarah Lindgren Belal, May Sadik, Reza Kaboteh, et al.
Clinical Physiology and Functional Imaging|September 25, 2020
Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survivalPablo Borrelli, Måns Larsson, Johannes Ulén, et al.
Radiation Protection Dosimetry|March 13, 2026
Comparison between artificial intelligence-based and manual organ delineations in pretreatment computed tomography scans of prostate cancer patients: a visual grading studyEirini Polymeri, Åse A Johnsson, Olof Enqvist, et al.
Pageof 5

Showing results (31-40 of 50) with videos related to

Sort By:
Pageof 5
Scientific Reports|December 14, 2021
Artificial intelligence based automatic quantification of epicardial adipose tissue suitable for large scale population studiesDavid Molnar, Olof Enqvist, Johannes Ulén, et al.
EJNMMI Research|February 27, 2026
Automated RECOMIA AI-based total metabolic tumor volume in lymphoma - a retrospective studyMay Sadik, Johanna Mörk, Jesus Lopez Urdaneta, et al.
Advances in Radiation Oncology|March 18, 2024
Artificial Intelligence-Based Organ Delineation for Radiation Treatment Planning of Prostate Cancer on Computed TomographyEirini Polymeri, Åse A Johnsson, Olof Enqvist, et al.
BMC Medical Imaging|September 17, 2025
Inter-reader agreement of quantitative FDG PET/CT biomarkers in lymphoma: a multicentre evaluation of MTV, TLG and DmaxElin Trägårdh, Malin Lewold, Jesus Lopez Urdaneta, et al.
Clinical Physiology and Functional Imaging|March 23, 2022
PET/CT imaging of spinal inflammation and microcalcification in patients with low back pain: A pilot study on the quantification by artificial intelligence-based segmentationReza Piri, Amalie H Nøddeskou-Fink, Oke Gerke, et al.
Diagnostics (Basel, Switzerland)|September 23, 2022
Freely Available, Fully Automated AI-Based Analysis of Primary Tumour and Metastases of Prostate Cancer in Whole-Body [<sup>18</sup>F]-PSMA-1007 PET-CTElin Trägårdh, Olof Enqvist, Johannes Ulén, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|August 13, 2021
"Global" cardiac atherosclerotic burden assessed by artificial intelligence-based versus manual segmentation in <sup>18</sup>F-sodium fluoride PET/CT scans: Head-to-head comparisonReza Piri, Lars Edenbrandt, Måns Larsson, et al.
European Journal of Radiology|April 1, 2019
Deep learning for segmentation of 49 selected bones in CT scans: First step in automated PET/CT-based 3D quantification of skeletal metastasesSarah Lindgren Belal, May Sadik, Reza Kaboteh, et al.
Clinical Physiology and Functional Imaging|September 25, 2020
Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survivalPablo Borrelli, Måns Larsson, Johannes Ulén, et al.
Radiation Protection Dosimetry|March 13, 2026
Comparison between artificial intelligence-based and manual organ delineations in pretreatment computed tomography scans of prostate cancer patients: a visual grading studyEirini Polymeri, Åse A Johnsson, Olof Enqvist, et al.
Pageof 5