Gross Tumor Volume

Gross Tumor Volume (GTV) delineation is crucial for radiotherapy planning in cancer treatment, particularly for head and neck cancers, as precise targeting maximizes efficacy while minimizing damage to healthy tissue. Current research heavily emphasizes automated GTV segmentation using deep learning models, including variations of U-Net and the Segment Anything Model (SAM), often incorporating multi-modal imaging data (CT, PET, MRI) to improve accuracy. These efforts aim to reduce inter-observer variability and the time burden of manual segmentation, ultimately improving treatment planning and patient outcomes. Ongoing challenges include robustly segmenting small or low-contrast tumors and adapting models across different hospitals and imaging protocols.