Shenzhen United Imaging Research Institute of Innovative Medical Equipment

To prospectively validate a prior and constraint-informed deep learning auto-segmentation framework for nasopharyngeal carcinoma (NPC) across three clinical centers, addressing accuracy, efficiency, and anatomical plausibility under real-world time constraint...

To generate physiologically plausible 4D medical image sequences from extremely sparse inputs by integrating external breathing signals, overcoming the limitation of requiring dense supervision in current spatiotemporal interpolation methods.

To evaluate a deep-learning based real-time automated radiotherapy planning pipeline for nasopharyngeal carcinoma (NPC) in both retrospective multi-center study and prospective clinical deployment.