Chengbao Xu

Deep learning for multimodal brain tumor segmentation: Architectures, fusion, robust learning, and deployment perspectives.

This survey critically reviews deep learning for multimodal brain tumor segmentation from a deployment-oriented, failure-focused perspective and introduces a unifying framework linking input reliability, fusion-architecture co-design, subregion-specific failure mechanisms, and uncertainty-aware clinical triage.