2 citations · 3 across the 4 of their papers we have counts for
Showing eess.IVShow all
3 papers · 1 filter
eess.IV2022★ 1 cited
Application of the nnU-Net for automatic segmentation of lung lesion on CT images, and implication on radiomic models
Matteo Ferrante, Lisa Rinaldi, Francesca Botta +17
Lesion segmentation is a crucial step of the radiomic workflow. Manual segmentation requires long execution time and is prone to variability, impairing the realisation of radiomic…
eess.IV2021★ 2 cited
Multi-Texture GAN: Exploring the Multi-Scale Texture Translation for Brain MR Images
Xiaobin Hu
Inter-scanner and inter-protocol discrepancy in MRI datasets are known to lead to significant quantification variability. Hence image-to-image or scanner-to-scanner translation is…
eess.IV2020
Feedback Graph Attention Convolutional Network for Medical Image Enhancement
Xiaobin Hu, Yanyang Yan, Wenqi Ren +4
Artifacts, blur and noise are the common distortions degrading MRI images during the acquisition process, and deep neural networks have been demonstrated to help in improving image…