277 citations · 291 across the 5 of their papers we have counts for
4 papers · 1 filter
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…