Intro
Preface
Organization
Contents - Part IV
Image Segmentation II
Category-Level Regularized Unlabeled-to-Labeled Learning for Semi-supervised Prostate Segmentation with Multi-site Unlabeled Data
1 Introduction
2 Methods
2.1 Problem Formulation and Basic Architecture
2.2 Pseudo Labeling for Local Distribution Fitting
2.3 Category-Level Regularized Unlabeled-to-Labeled Learning
3 Experiments and Results
4 Conclusion
References
Devil is in Channels: Contrastive Single Domain Generalization for Medical Image Segmentation
1 Introduction
2 Method

2.1 Problem Definition and Method Overview
2.2 Style Augmentation
2.3 Contrastive Feature Disentanglement
2.4 Training and Inference
3 Experiments and Results
4 Conclusion
References
Transformer-Based Annotation Bias-Aware Medical Image Segmentation
1 Introduction
2 Method
2.1 Problem Formalization and Method Overview
2.2 CNN Encoder
2.3 PFE Module
2.4 SS Head
2.5 Loss and Inference
3 Experiments and Results
3.1 Dataset and Experimental Setup
3.2 Comparative Experiments
3.3 Ablation Analysis
4 Conclusion
References

Uncertainty-Informed Mutual Learning for Joint Medical Image Classification and Segmentation
1 Introduction
2 Method
2.1 Uncertainty Estimation for Classification and Segmentation
2.2 Uncertainty-Informed Mutual Learning
2.3 Mutual Learning Process
3 Experiments
4 Conclusion
References
A General Stitching Solution for Whole-Brain 3D Nuclei Instance Segmentation from Microscopy Images
1 Introduction
2 Methods
2.1 Graph Contextual Model
2.2 Hierarchical Stitching Framework for Whole-Brain NIS
2.3 Implementation Details
3 Experiments

3.1 Experimental Settings
3.2 Evaluation Metrics
3.3 Evaluating the Accuracy of NIS Stitching Results
3.4 Whole-Brain NIS in Neuroscience Applications
4 Conclusion
References
Adult-Like Phase and Multi-scale Assistance for Isointense Infant Brain Tissue Segmentation
1 Introduction
2 Methods
2.1 Semantics-Preserved Multi-phase Synthesis
2.2 Transformer-Based Multi-scale Segmentation
3 Experiments and Results
3.1 Dataset and Evaluation Metrics
3.2 Implementation Details
3.3 Evaluation and Discussion
4 Conclusion
References

Robust Segmentation via Topology Violation Detection and Feature Synthesis
1 Introduction
2 Method
3 Evaluation
4 Conclusion
References
GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video Segmentation
1 Introduction
2 Methodology
2.1 The Overall Framework
2.2 Multi-view Global-Local Fusion Module
2.3 Dense Cycle Loss
3 Experiment
3.1 Comparison with the State-of-the-Art Methods
3.2 Ablation Study
4 Conclusion
References