Impact of light field compression on focus stack and extended focus images. - Mira Rizkallah; Thomas Maugey; Charles Yaacoub; Christine Guillemot (EUSIPCO, 2016)

Graph-based light fields representation and coding using geometry information. - Xin Su 003; Mira Rizkallah; Thomas Maugey; Christine Guillemot (ICIP, 2017)

Rate-Distortion Optimized Super-Ray Merging for Light Field Compression. - Xin Su 003; Mira Rizkallah; Thomas Mauzev; Christine Guillemot (EUSIPCO, 2018)

Rate Distortion Optimized Graph Partitioning for Omnidirectional Image Coding. - Mira Rizkallah; Francesca De Simone; Thomas Maugey; Christine Guillemot; Pascal Frossard (EUSIPCO, 2018)

Graph-based Transforms for Predictive Light Field Compression based on Super-Pixels. - Mira Rizkallah; Xin Su 003; Thomas Maugey; Christine Guillemot (ICASSP, 2018)

Graph-Based Spatio-Angular Prediction for Quasi-Lossless Compression of Light Fields. - Mira Rizkallah; Thomas Maugey; Christine Guillemot (DCC, 2019)

Graph based transforms for compression of new imaging modalities. (Transformées basées graphes pour la compression de nouvelles modalités d'image). - Mira Rizkallah (2019)

Geometry-Aware Graph Transforms for Light Field Compact Representation. - Mira Rizkallah; Xin Su 003; Thomas Maugey; Christine Guillemot (IEEE Trans. Image Process., 2020)

Prediction and Sampling With Local Graph Transforms for Quasi-Lossless Light Field Compression. - Mira Rizkallah; Thomas Maugey; Christine Guillemot (IEEE Trans. Image Process., 2020)

Unsupervised Multimodal Supervoxel Merging Towards Brain Tumor Segmentation. - Guillaume Pelluet; Mira Rizkallah; Oscar Acosta; Diana Mateus (BrainLes@MICCAI (1), 2021)

Rate-Distortion Optimized Graph Coarsening and Partitioning for Light Field Coding. - Mira Rizkallah; Thomas Maugey; Christine Guillemot (IEEE Trans. Image Process., 2021)

Multi-scale Graph Neural Networks for Mammography Classification and Abnormality Detection. - Guillaume Pelluet; Mira Rizkallah; Mickael Tardy; Oscar Acosta; Diana Mateus (MIUA, 2022)

Lesion Graph Neural Networks for 2-Year Progression Free Survival Classification of Diffuse Large B-Cell Lymphoma Patients. - Aswathi Aswathi; Mira Rizkallah; Gauthier Frecon; Clément Bailly; Caroline Bodet-Milin; Olivier Casasnovas; Steven Le Gouill; Françoise Kraeber-Bodéré; Thomas Carlier; Diana Mateus (ISBI, 2023)

Graph-Based Multimodal Multi-lesion DLBCL Treatment Response Prediction from PET Images. - Oriane Thiery; Mira Rizkallah; Clément Bailly; Caroline Bodet-Milin; Emmanuel Itti; René-Olivier Casasnovas; Steven Le Gouill; Thomas Carlier; Diana Mateus (MTSAIL/LEAF/AI4Treat/MMMI/REMIA@MICCAI, 2023)

Functional Graph Image Representation applied to EEG-based Mental Workload Classification. - Maria Sarkis; Mira Rizkallah; Saïd Moussaoui (EMBC, 2024)

Graph Force Learning from EEG Signals for Mental Workload Classification. - Maria Sarkis; Mira Rizkallah; Saïd Moussaoui (SSP, 2025)

PET-based lesion graphs meet clinical data: An interpretable cross-attention framework for DLBCL treatment response prediction. - Oriane Thiery; Mira Rizkallah; Clément Bailly; Caroline Bodet-Milin; Emmanuel Itti; René-Olivier Casasnovas; Steven Le Gouill; Thomas Carlier; Diana Mateus (Comput. Medical Imaging Graph., 2025)