Automatic Myocardial Scar Segmentation from Multi-sequence Cardiac MRI Using Fully Convolutional Densenet with Inception and Squeeze-Excitation Module. - Tewodros Weldebirhan Arega; Stéphanie Bricq (MyoPS@MICCAI, 2020)

Leveraging Uncertainty Estimates to Improve Segmentation Performance in Cardiac MR. - Tewodros Weldebirhan Arega; Stéphanie Bricq; Fabrice Mériaudeau (UNSURE/PIPPI@MICCAI, 2021)

Using MRI-specific Data Augmentation to Enhance the Segmentation of Right Ventricle in Multi-disease, Multi-center and Multi-view Cardiac MRI. - Tewodros Weldebirhan Arega; François Le Grand; Stéphanie Bricq; Fabrice Mériaudeau (STACOM@MICCAI, 2021)

Using Polynomial Loss and Uncertainty Information for Robust Left Atrial and Scar Quantification and Segmentation. - Tewodros Weldebirhan Arega; Stéphanie Bricq; Fabrice Mériaudeau (LAScarQS@MICCAI, 2022)

Automatic Quality Assessment of Cardiac MR Images with Motion Artefacts Using Multi-task Learning and K-Space Motion Artefact Augmentation. - Tewodros Weldebirhan Arega; Stéphanie Bricq; Fabrice Mériaudeau (STACOM@MICCAI, 2022)

An Improved 3D Deep Learning-Based Segmentation of Left Ventricular Myocardial Diseases from Delayed-Enhancement MRI with Inclusion and Classification Prior Information U-Net (ICPIU-Net). - Khawla Brahim; Tewodros Weldebirhan Arega; Arnaud Boucher; Stéphanie Bricq; Anis Sakly; Fabrice Mériaudeau (Sensors, 2022)

Using Uncertainty Information for Kidney Tumor Segmentation. - Joffrey Michaud; Tewodros Weldebirhan Arega; Stéphanie Bricq (KiTS@MICCAI, 2023)

MyoPS: A benchmark of myocardial pathology segmentation combining three-sequence cardiac magnetic resonance images. - Lei Li 020; Fuping Wu; Sihan Wang; Xinzhe Luo; Carlos Martín-Isla; Shuwei Zhai; Jianpeng Zhang; Yanfei Liu; Zhen Zhang 057; Markus J. Ankenbrand; Haochuan Jiang; Xiaoran Zhang; et al. (Medical Image Anal., 2023)

Uncertainty-based Deep Learning Methods for Robust and Reliable Cardiac MRI Segmentation and Analysis. (Méthodes d'apprentissage profond basées sur l'incertitude pour une segmentation et une analyse robustes et fiables de l'IRM cardiaque). - Tewodros Weldebirhan Arega (2023)

Automatic uncertainty-based quality controlled T1 mapping and ECV analysis from native and post-contrast cardiac T1 mapping images using Bayesian vision transformer. - Tewodros Weldebirhan Arega; Stéphanie Bricq; François Le Grand; Alexis Jacquier; Alain Lalande; Fabrice Mériaudeau (Medical Image Anal., 2023)

Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge. - Carlos Martín-Isla; Víctor M. Campello; Cristian Izquierdo; Kaisar Kushibar; Carla Sendra-Balcells; Polyxeni Gkontra; Alireza Sojoudi; Mitchell J. Fulton; Tewodros Weldebirhan Arega; Kumaradevan Punithakumar; Lei Li 020; Xiaowu Sun; et al. (IEEE J. Biomed. Health Informatics, 2023)

Post-hoc out-of-distribution detection for cardiac MRI segmentation. - Tewodros Weldebirhan Arega; Stéphanie Bricq; Fabrice Mériaudeau (Comput. Medical Imaging Graph., 2025)

Extreme Cardiac MRI Analysis under Respiratory Motion: Results of the CMRxMotion Challenge. - Kang Wang 004; Chen Qin; Zhang Shi; Haoran Wang 009; Xiwen Zhang; Chen Chen 042; Cheng Ouyang; Chengliang Dai; Yuanhan Mo; Chenchen Dai; Xutong Kuang; Ruizhe Li; et al. (CoRR, 2025)