Nasopharyngeal Carcinoma

Nasopharyngeal carcinoma (NPC) research focuses on improving diagnosis, treatment planning, and prognosis prediction, primarily leveraging advanced imaging techniques like MRI and CT scans. Current research employs deep learning architectures, including DenseNet, U-Net variations, and contrastive learning methods, to analyze multi-modal imaging data for accurate tumor segmentation and organ-at-risk delineation, crucial for radiotherapy planning. These efforts aim to improve the accuracy and efficiency of NPC diagnosis and treatment, ultimately leading to better patient outcomes. The development of large, publicly available datasets is also a key focus to facilitate further advancements in the field.