Neck Cancer

Neck cancer research focuses on improving diagnosis, treatment planning, and prognosis prediction, primarily leveraging advanced imaging techniques like PET/CT and MRI. Current efforts utilize deep learning models, including convolutional neural networks (CNNs), vision transformers (ViTs), and recurrent neural networks, for tasks such as automated tumor segmentation, organ-at-risk delineation, and survival prediction, often incorporating radiomics features. These advancements aim to improve the accuracy, efficiency, and reproducibility of clinical workflows, ultimately leading to better patient outcomes and personalized treatment strategies.