Intelligent recognition and segmentation of anatomical structures in spinal endoscopy: a deep learning approach with 1000 annotated images.

This study presents a promising segmentation system for spinal endoscopic anatomy that achieves high accuracy for critical soft tissues such as the ligamentum flavum and nerve roots.

The integration of attention mechanisms and multi-scale feature extraction proves to be an effective strategy.

However, the current accuracy for posterior longitudinal ligament and bone remains insufficient for clinical use, and further refinement is required before real-time navigation can be considered.