Cardiac MRI Segmentation with Strong Anatomical Guarantees. - Nathan Painchaud; Youssef Skandarani; Thierry Judge; Olivier Bernard 001; Alain Lalande; Pierre-Marc Jodoin (MICCAI (2), 2019)

On the effectiveness of GAN generated cardiac MRIs for segmentation. - Youssef Skandarani; Nathan Painchaud; Pierre-Marc Jodoin; Alain Lalande (CoRR, 2020)

Neural Teleportation. - Marco Antonio Armenta; Thierry Judge; Nathan Painchaud; Youssef Skandarani; Carl Lemaire; Gabriel Gibeau Sanchez; Philippe Spino; Pierre-Marc Jodoin (CoRR, 2020)

Cardiac Segmentation With Strong Anatomical Guarantees. - Nathan Painchaud; Youssef Skandarani; Thierry Judge; Olivier Bernard 001; Alain Lalande; Pierre-Marc Jodoin (IEEE Trans. Medical Imaging, 2020)

Echocardiography Segmentation With Enforced Temporal Consistency. - Nathan Painchaud; Nicolas Duchateau; Olivier Bernard 001; Pierre-Marc Jodoin (IEEE Trans. Medical Imaging, 2022)

Extraction of Volumetric Indices from Echocardiography: Which Deep Learning Solution for Clinical Use? - Hang Jung Ling; Nathan Painchaud; Pierre-Yves Courand; Pierre-Marc Jodoin; Damien Garcia; Olivier Bernard 001 (FIMH, 2023)

Fusing Echocardiography Images and Medical Records for Continuous Patient Stratification. - Nathan Painchaud; Pierre-Yves Courand; Pierre-Marc Jodoin; Nicolas Duchateau; Olivier Bernard 001 (CoRR, 2024)

Apprentissage profond de variétés pour une meilleure caractérisation de l'hypertension artérielle en imagerie échocardiographique. (Deep manifold learning for improved high blood pressure characterization using echocardiography). - Nathan Painchaud (2024)