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Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution |
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Title: |
Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution |
Author: |
Djahnine, Aissam Lazarus, Carole Lederlin, Mathieu Mulé, Sébastien Wiemker, Rafael Si-Mohamed, Salim Jupin-Delevaux, Emilien Nempont, Olivier Skandarani, Youssef De Craene, Mathieu Goubalan, Segbedji Raynaud, Caroline Belkouchi, Younes Afia, Amira Ben Fabre, Clement Ferretti, Gilbert De Margerie, Constance Berge, Pierre Liberge, Renan Elbaz, Nicolas Blain, Maxime Brillet, Pierre-Yves Chassagnon, Guillaume Cadour, Farah Caramella, Caroline Hajjam, Mostafa El Boussouar, Samia Hadchiti, Joya Fablet, Xavier Khalil, Antoine Talbot, Hugues Luciani, Alain Lassau, Nathalie Boussel, Loic |
Appeared in: |
Diagnostic and interventional imaging |
Paging: |
Volume 105 () nr. 3 pages 97-103 |
Year: |
2024 |
Contents: |
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Publisher: |
Société française de radiologie |
Source file: |
Elektronische Wetenschappelijke Tijdschriften |
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