1 citations · 1 across the 3 of their papers we have counts for
4 papers
A 3D mesh convolution-based autoencoder for geometry compression
Germain Bregeon, Marius Preda, Radu Ispas +1
In this paper, we introduce a novel 3D mesh convolution-based autoencoder for geometry compression, able to deal with irregular mesh data without requiring neither preprocessing no…
MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes
Germain Bregeon, Marius Preda, Radu Ispas +1
Convolutional neural networks (CNNs) have been pivotal in various 2D image analysis tasks, including computer vision, image indexing and retrieval or semantic classification. Exten…
Diff-Lung: Diffusion-Based Texture Synthesis for Enhanced Pathological Tissue Segmentation in Lung CT Scans
Rezkellah Noureddine Khiati, Pierre-Yves Brillet, Radu Ispas +1
Accurate quantification of the extent of lung pathological patterns (fibrosis, ground-glass opacity, emphysema, consolidation) is prerequisite for diagnosis and follow-up of inters…
Shape-aware synthesis of pathological lung CT scans using CycleGAN for enhanced semi-supervised lung segmentation
Rezkellah Noureddine Khiati, Pierre-Yves Brillet, Aurélien Justet +2
This paper addresses the problem of pathological lung segmentation, a significant challenge in medical image analysis, particularly pronounced in cases of peripheral opacities (sev…