1 citations · 1 across the 4 of their papers we have counts for
4 papers
Cross-Sequence Semi-Supervised Learning for Multi-Parametric MRI-Based Visual Pathway Delineation
Alou Diakite, Cheng Li, Lei Xie +5
Accurately delineating the visual pathway (VP) is crucial for understanding the human visual system and diagnosing related disorders. Exploring multi-parametric MR imaging data has…
Knowledge-driven deep learning for fast MR imaging: undersampled MR image reconstruction from supervised to un-supervised learning
Shanshan Wang, Ruoyou Wu, Sen Jia +4
Deep learning (DL) has emerged as a leading approach in accelerating MR imaging. It employs deep neural networks to extract knowledge from available datasets and then applies the t…
Modality Exchange Network for Retinogeniculate Visual Pathway Segmentation
Hua Han, Cheng Li, Lei Xie +3
Accurate segmentation of the retinogeniculate visual pathway (RGVP) aids in the diagnosis and treatment of visual disorders by identifying disruptions or abnormalities within the p…
LESEN: Label-Efficient deep learning for Multi-parametric MRI-based Visual Pathway Segmentation
Alou Diakite, Cheng Li, Lei Xie +3
Recent research has shown the potential of deep learning in multi-parametric MRI-based visual pathway (VP) segmentation. However, obtaining labeled data for training is laborious a…