277 citations · 291 across the 5 of their papers we have counts for
6 papers
Multi-Task Diffusion Approach For Prediction of Glioma Tumor Progression
Aghiles Kebaili, Romain Modzelewski, Jérôme Lapuyade-Lahorgue +3
Glioma, an aggressive brain malignancy characterized by rapid progression and its poor prognosis, poses significant challenges for accurate evolution prediction. These challenges a…
AMM-Diff: Adaptive Multi-Modality Diffusion Network for Missing Modality Imputation
Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera +1
In clinical practice, full imaging is not always feasible, often due to complex acquisition protocols, stringent privacy regulations, or specific clinical needs. However, missing M…
Discriminative Hamiltonian Variational Autoencoder for Accurate Tumor Segmentation in Data-Scarce Regimes
Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera +1
Deep learning has gained significant attention in medical image segmentation. However, the limited availability of annotated training data presents a challenge to achieving accurat…
3D MRI Synthesis with Slice-Based Latent Diffusion Models: Improving Tumor Segmentation Tasks in Data-Scarce Regimes
Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera +1
Despite the increasing use of deep learning in medical image segmentation, the limited availability of annotated training data remains a major challenge due to the time-consuming d…
End-to-end autoencoding architecture for the simultaneous generation of medical images and corresponding segmentation masks
Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera +1
Despite the increasing use of deep learning in medical image segmentation, acquiring sufficient training data remains a challenge in the medical field. In response, data augmentati…
Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review
Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Su Ruan
Deep learning has become a popular tool for medical image analysis, but the limited availability of training data remains a major challenge, particularly in the medical field where…