Assessing the robustness and clinical evaluation of a deep−learning segmentation model for head and neck cancer

DL-based PET/CT segmentation models for HNC show strong baseline performance and robustness for primary tumors. However, nodal tumor segmentation remains vulnerable to specific image artifacts. Enhancing robustness through targeted data augmentation and validation under variable conditions is essential for clinical integration.