Multimodal Deep Learning and Knowledge-Enhanced Intelligent Decision Support System for Pipeline Embolization Device Size Selection in Intracranial Aneurysm Treatment.

NeurAneuNet achieved a Dice coefficient of 0.874 ± 0.03 for aneurysm segmentation, a Pipeline Embolization Device size classification accuracy of 91.8%, and a diameter prediction error of 0.24 ± 0.10 mm.

When assisting clinicians, the system reduced planning time by 44.8% and significantly lowered subjective cognitive workload, as assessed by the National Aeronautics and Space Administration Task Load Index (NASA-TLX) score (from 33 ± 8 to 21 ± 5).