9 citations · 14 across the 7 of their papers we have counts for
4 papers · 1 filter
Self-Prior Guided Mamba-UNet Networks for Medical Image Super-Resolution
Zexin Ji, Beiji Zou, Xiaoyan Kui +2
In this paper, we propose a self-prior guided Mamba-UNet network (SMamba-UNet) for medical image super-resolution. Existing methods are primarily based on convolutional neural netw…
Deform-Mamba Network for MRI Super-Resolution
Zexin Ji, Beiji Zou, Xiaoyan Kui +2
In this paper, we propose a new architecture, called Deform-Mamba, for MR image super-resolution. Unlike conventional CNN or Transformer-based super-resolution approaches which enc…
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…