Medical Image Analysis

1. High-frequency structure transformer for magnetic resonance image super-resolution

Magnetic Resonance (MR) imaging is essential in clinical diagnostics due to its ability to capture detailed soft tissue structures. However, acquiring high-resolution MR images is expensive and often leads to reduced signal-to-noise ratios. To …

2. Multi-task Learning with Hierarchical Guidance for Locating and Stratifying Submucosal Tumors

3. Reliable Mutual Distillation for Medical Image Segmentation under Imperfect Annotations

Convolutional neural networks (CNNs) have made enormous progress in medical image segmentation. The learning of CNNs is dependent on a large amount of training data with fine annotations. The workload of data labeling can be significantly relieved …

4. Cross-Modality High-Frequency Transformer for MR Image Super-Resolution

5. Gradient-Rebalanced Uncertainty Minimization for Cross-Site Adaptation of Medical Image Segmentation

6. Incremental Cross-view Mutual Distillation for Self-supervised Medical CT Synthesis

7. Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image Segmentation

8. Interactive Dual-Model Learning for Semi-supervised Medical Image Segmentation (in Chinese)

9. M3Net: A Multi-scale Multi-view Framework for Multi-phase Pancreas Segmentation Based on Cross-phase Non-local Attention

The complementation of arterial and venous phases visual information of CTs can help better distinguish the pancreas from its surrounding structures. However, the exploration of cross-phase contextual information is still under research in …

10. Contralaterally Enhanced Networks for Thoracic Disease Detection

Identifying and locating diseases in chest Xrays are very challenging, due to the low visual contrast between normal and abnormal regions, and distortions caused by other overlapping tissues. An interesting phenomenon is that there exist many similar …