CLoE: Expert Consistency Learning for Robust Missing Modality Segmentation

1. 1Formulate robustness as decision-level expert consistency using CLoE
2. 2Implement CLoE framework for missing-modality segmentation
3. 3Train modality experts using consistency-driven learning
4. 4Evaluate CLoE on multimodal medical image datasets
5. 5Fine-tune CLoE for improved performance on small foreground structures

Data scientists and AI engineers working on medical image analysis can benefit from CLoE to improve the robustness of their segmentation models, particularly in situations where modalities are missing

💡 CLoE preserves strong performance when all modalities are available by learning consistency among modality experts

📸 Improve robust missing modality segmentation in medical images with CLoE! 💡