Oral Cancer

Oral cancer research focuses on improving early detection and treatment planning, driven by the need for faster, less invasive diagnostic tools and more accurate treatment targeting. Current efforts leverage deep learning, particularly convolutional neural networks (CNNs) and U-Net architectures, to analyze various image modalities (e.g., H&E stained histology, FDG PET/CT scans) for automated segmentation and classification of cancerous tissue. These advancements aim to enhance diagnostic accuracy, personalize treatment strategies, and ultimately improve patient outcomes by facilitating earlier intervention and more precise radiotherapy.