activity
20212024
most citedSemi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer

100 citations · 105 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2024

Self-Consistent Nested Diffusion Bridge for Accelerated MRI Reconstruction

Tao Song, Yicheng Wu, Minhao Hu +6

Accelerated MRI reconstruction plays a vital role in reducing scan time while preserving image quality. While most existing methods rely on complex-valued image-space or k-space da…

eess.IV2024

Learning Modality-Aware Representations: Adaptive Group-wise Interaction Network for Multimodal MRI Synthesis

Tao Song, Yicheng Wu, Minhao Hu +6

Multimodal MR image synthesis aims to generate missing modality images by effectively fusing and mapping from a subset of available MRI modalities. Most existing methods adopt an i…

eess.IV2022★ 5 cited

Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision

Xiangde Luo, Minhao Hu, Wenjun Liao +4

Medical image segmentation plays an irreplaceable role in computer-assisted diagnosis, treatment planning, and following-up. Collecting and annotating a large-scale dataset is cruc…

eess.IV2021★ 100 cited

Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer

Xiangde Luo, Minhao Hu, Tao Song +2

Recently, deep learning with Convolutional Neural Networks (CNNs) and Transformers has shown encouraging results in fully supervised medical image segmentation. However, it is stil…

cs.CV2021

Knowledge distillation from multi-modal to mono-modal segmentation networks

Minhao Hu, Matthis Maillard, Ya Zhang +4

The joint use of multiple imaging modalities for medical image segmentation has been widely studied in recent years. The fusion of information from different modalities has demonst…