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Joris Fournel

Showing results (1-10 of 9) with videos related to

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Danish Medical Journal|April 14, 2026
Risks of automation in medicine - a review article for the obstetrics caseJoris Fournel, Aasa Feragen, Martin Tolsgaard
Medical Image Analysis|August 29, 2021
Medical image segmentation automatic quality control: A multi-dimensional approachJoris Fournel, Axel Bartoli, David Bendahan, et al.
Radiology. Artificial Intelligence|May 3, 2021
Deep Learning-based Automated Segmentation of Left Ventricular Trabeculations and Myocardium on Cardiac MR Images: A Feasibility StudyAxel Bartoli, Joris Fournel, Zakarya Bentatou, et al.
Radiology|April 2, 2024
Left Ventricular Trabeculations at Cardiac MRI: Reference Ranges and Association with Cardiovascular Risk Factors in UK BiobankNay Aung, Axel Bartoli, Elisa Rauseo, et al.
Cells|March 25, 2022
Automatic Deep-Learning Segmentation of Epicardial Adipose Tissue from Low-Dose Chest CT and Prognosis Impact on COVID-19Axel Bartoli, Joris Fournel, Léa Ait-Yahia, et al.
European Radiology|November 7, 2025
Deep learning-driven false-lumen volumes predict adverse remodeling better than diameter in patients with residual aortic dissection on CTJoris Fournel, Mariangela De Masi, Charlotte Lu, et al.
Diabetes & Metabolism|February 2, 2026
Increased epicardial adipose tissue is part of the phenotype of LMNA-associated partial lipodystrophy and could contribute to increased cardiovascular riskSophie Lamothe, Patricia Ancel, Inès Belalem, et al.
Research in Diagnostic and Interventional Imaging|July 31, 2023
Value and prognostic impact of a deep learning segmentation model of COVID-19 lung lesions on low-dose chest CTAxel Bartoli, Joris Fournel, Arnaud Maurin, et al.
Cardiovascular Diabetology|September 3, 2024
Fully automated epicardial adipose tissue volume quantification with deep learning and relationship with CAC score and micro/macrovascular complications in people living with type 2 diabetes: the multicenter EPIDIAB studyBénédicte Gaborit, Jean Baptiste Julla, Joris Fournel, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Danish Medical Journal|April 14, 2026
Risks of automation in medicine - a review article for the obstetrics caseJoris Fournel, Aasa Feragen, Martin Tolsgaard
Medical Image Analysis|August 29, 2021
Medical image segmentation automatic quality control: A multi-dimensional approachJoris Fournel, Axel Bartoli, David Bendahan, et al.
Radiology. Artificial Intelligence|May 3, 2021
Deep Learning-based Automated Segmentation of Left Ventricular Trabeculations and Myocardium on Cardiac MR Images: A Feasibility StudyAxel Bartoli, Joris Fournel, Zakarya Bentatou, et al.
Radiology|April 2, 2024
Left Ventricular Trabeculations at Cardiac MRI: Reference Ranges and Association with Cardiovascular Risk Factors in UK BiobankNay Aung, Axel Bartoli, Elisa Rauseo, et al.
Cells|March 25, 2022
Automatic Deep-Learning Segmentation of Epicardial Adipose Tissue from Low-Dose Chest CT and Prognosis Impact on COVID-19Axel Bartoli, Joris Fournel, Léa Ait-Yahia, et al.
European Radiology|November 7, 2025
Deep learning-driven false-lumen volumes predict adverse remodeling better than diameter in patients with residual aortic dissection on CTJoris Fournel, Mariangela De Masi, Charlotte Lu, et al.
Diabetes & Metabolism|February 2, 2026
Increased epicardial adipose tissue is part of the phenotype of LMNA-associated partial lipodystrophy and could contribute to increased cardiovascular riskSophie Lamothe, Patricia Ancel, Inès Belalem, et al.
Research in Diagnostic and Interventional Imaging|July 31, 2023
Value and prognostic impact of a deep learning segmentation model of COVID-19 lung lesions on low-dose chest CTAxel Bartoli, Joris Fournel, Arnaud Maurin, et al.
Cardiovascular Diabetology|September 3, 2024
Fully automated epicardial adipose tissue volume quantification with deep learning and relationship with CAC score and micro/macrovascular complications in people living with type 2 diabetes: the multicenter EPIDIAB studyBénédicte Gaborit, Jean Baptiste Julla, Joris Fournel, et al.
Pageof 1