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Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution

Aissam Djahnine, Carole Lazarus, Mathieu Léderlin, Sebastien Mulé, Rafael Wiemker, Salim Si‐Mohamed, Émilien Jupin-Delevaux, Olivier Nempont, Youssef Skandarani, Mathieu De Craene, Sègbédji R. T. J. Goubalan, Caroline Raynaud, Younes Belkouchi, Amira Ben Afia, Clement Fabre, G. Ferretti, Constance de Margerie‐Mellon, Pierre Berge, Renan Liberge, Nicolas Elbaz, Maxime Blain, Pierre‐Yves Brillet, Guillaume Chassagnon, Farah Cadour, Caroline Caramella, Mostafa El Hajjam, Samia Boussouar, Joya Hadchiti, Xavier Fablet, Antoine Khalil, Hugues Talbot, Alain Luciani, Nathalie Lassau, Loïc Boussel

2023Diagnostic and Interventional Imaging25 citationsDOIOpen Access PDF

Topics & Concepts

MedicinePulmonary embolismVentricleRadiologyDeep learningComputed tomography angiographyPulmonary angiographyComputed tomographyArtificial intelligenceCardiologyComputer scienceVenous Thromboembolism Diagnosis and ManagementAtrial Fibrillation Management and OutcomesCerebral Venous Sinus Thrombosis
Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution | Litcius