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Clinical Physiology and Functional Imaging
|
August 23, 2019
Artificial intelligence-based versus manual assessment of prostate cancer in the prostate gland: a method comparison study
Mike A Mortensen, Pablo Borrelli, Mads Hvid Poulsen, et al.
Scandinavian Journal of Urology
|
September 27, 2021
Artificial intelligence-based measurements of PET/CT imaging biomarkers are associated with disease-specific survival of high-risk prostate cancer patients
Eirini Polymeri, Henrik Kjölhede, Olof Enqvist, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
July 26, 2023
Application of an artificial intelligence-based tool in [<sup>18</sup>F]FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma
Christos Sachpekidis, Olof Enqvist, Johannes Ulén, et al.
EJNMMI Research
|
February 18, 2017
3D skeletal uptake of <sup>18</sup>F sodium fluoride in PET/CT images is associated with overall survival in patients with prostate cancer
Sarah Lindgren Belal, May Sadik, Reza Kaboteh, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
February 21, 2025
Correction to: Artificial intelligence-based, volumetric assessment of the bone marrow metabolic activity in [<sup>18</sup>F]FDG PET/CT predicts survival in multiple myeloma
Christos Sachpekidis, Olof Enqvist, Johannes Ulén, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
March 8, 2024
Artificial intelligence-based, volumetric assessment of the bone marrow metabolic activity in [<sup>18</sup>F]FDG PET/CT predicts survival in multiple myeloma
Christos Sachpekidis, Olof Enqvist, Johannes Ulén, et al.
EJNMMI Research
|
May 22, 2019
Correction to: 3D skeletal uptake of <sup>18</sup>F sodium fluoride in PET/CT images is associated with overall survival in patients with prostate cancer
Sarah Lindgren Belal, May Sadik, Reza Kaboteh, et al.
Clinical Physiology and Functional Imaging
|
December 4, 2019
Deep learning-based quantification of PET/CT prostate gland uptake: association with overall survival
Eirini Polymeri, May Sadik, Reza Kaboteh, et al.
Hematology Reports
|
November 24, 2025
AI Improves Agreement and Reduces Time for Quantifying Metabolic Tumour Burden in Hodgkin Lymphoma
May Sadik, Sally F Barrington, Johannes Ulén, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
October 1, 2025
Validation of novel low-dose CT methods for quantifying bone marrow in the appendicular skeleton of patients with multiple myeloma: initial results from the [<sup>18</sup>F]FDG PET/CT sub-study of the Phase 3 GMMG-HD7 Trial
Christos Sachpekidis, Marina Hajiyianni, Martin Grözinger, et al.
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Search research articles
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Showing results (41-50 of 50) with videos related to
Sort By:
Page
of 5
You have reached the last page of results.
This site can display upto 50 results.
Clinical Physiology and Functional Imaging
|
August 23, 2019
Artificial intelligence-based versus manual assessment of prostate cancer in the prostate gland: a method comparison study
Mike A Mortensen, Pablo Borrelli, Mads Hvid Poulsen, et al.
Scandinavian Journal of Urology
|
September 27, 2021
Artificial intelligence-based measurements of PET/CT imaging biomarkers are associated with disease-specific survival of high-risk prostate cancer patients
Eirini Polymeri, Henrik Kjölhede, Olof Enqvist, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
July 26, 2023
Application of an artificial intelligence-based tool in [<sup>18</sup>F]FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma
Christos Sachpekidis, Olof Enqvist, Johannes Ulén, et al.
EJNMMI Research
|
February 18, 2017
3D skeletal uptake of <sup>18</sup>F sodium fluoride in PET/CT images is associated with overall survival in patients with prostate cancer
Sarah Lindgren Belal, May Sadik, Reza Kaboteh, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
February 21, 2025
Correction to: Artificial intelligence-based, volumetric assessment of the bone marrow metabolic activity in [<sup>18</sup>F]FDG PET/CT predicts survival in multiple myeloma
Christos Sachpekidis, Olof Enqvist, Johannes Ulén, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
March 8, 2024
Artificial intelligence-based, volumetric assessment of the bone marrow metabolic activity in [<sup>18</sup>F]FDG PET/CT predicts survival in multiple myeloma
Christos Sachpekidis, Olof Enqvist, Johannes Ulén, et al.
EJNMMI Research
|
May 22, 2019
Correction to: 3D skeletal uptake of <sup>18</sup>F sodium fluoride in PET/CT images is associated with overall survival in patients with prostate cancer
Sarah Lindgren Belal, May Sadik, Reza Kaboteh, et al.
Clinical Physiology and Functional Imaging
|
December 4, 2019
Deep learning-based quantification of PET/CT prostate gland uptake: association with overall survival
Eirini Polymeri, May Sadik, Reza Kaboteh, et al.
Hematology Reports
|
November 24, 2025
AI Improves Agreement and Reduces Time for Quantifying Metabolic Tumour Burden in Hodgkin Lymphoma
May Sadik, Sally F Barrington, Johannes Ulén, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
October 1, 2025
Validation of novel low-dose CT methods for quantifying bone marrow in the appendicular skeleton of patients with multiple myeloma: initial results from the [<sup>18</sup>F]FDG PET/CT sub-study of the Phase 3 GMMG-HD7 Trial
Christos Sachpekidis, Marina Hajiyianni, Martin Grözinger, et al.
Page
of 5