End-to-End Autoencoding Architecture for the Simultaneous Generation of Medical Images and Corresponding Segmentation Masks. - Aghiles Kebaili; Jérôme Lapuyade-Lahorgue; Pierre Vera; Su Ruan (MICAD, 2023)

Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review. - Aghiles Kebaili; Jérôme Lapuyade-Lahorgue; Su Ruan (J. Imaging, 2023)

3D MRI Synthesis with Slice-Based Latent Diffusion Models: Improving Tumor Segmentation Tasks in Data-Scarce Regimes. - Aghiles Kebaili; Jérôme Lapuyade-Lahorgue; Pierre Vera; Su Ruan (ISBI, 2024)

Discriminative Hamiltonian variational autoencoder for accurate tumor segmentation in data-scarce regimes. - Aghiles Kebaili; Jérôme Lapuyade-Lahorgue; Pierre Vera; Su Ruan (Neurocomputing, 2024)

AMM-Diff: Adaptive Multi-Modality Diffusion Network for Missing Modality Imputation. - Aghiles Kebaili; Jérôme Lapuyade-Lahorgue; Pierre Vera; Su Ruan (ISBI, 2025)

Multi-modal MRI synthesis with conditional latent diffusion models for data augmentation in tumor segmentation. - Aghiles Kebaili; Jérôme Lapuyade-Lahorgue; Pierre Vera; Su Ruan (Comput. Medical Imaging Graph., 2025)