Anatomy-informed deep learning and radiomics for neurofibroma segmentation in whole-body MRI

The proposed pipeline achieves the highest performance among established methods for automated NF segmentation in WB-MRI and approaches expert-level consistency. The integration of anatomical context and radiomics enhances robustness. Nonetheless, segmentation performance decreases in low tumor burden scenarios, indicating a key area for future methodological improvements. Additionally, the limited inter-reader agreement observed among experts underscores the inherent complexity and ambiguity of the NF segmentation task.