Pancreatic Cancer

Pancreatic cancer research intensely focuses on improving early detection and treatment planning, primarily through advanced image analysis techniques. Current efforts leverage deep learning models, including U-Net variations, GANs, and transformer networks, to achieve accurate segmentation of tumors and surrounding vasculature from CT and endoscopic ultrasound images, often addressing data scarcity through synthetic data generation or weakly supervised learning. These advancements aim to improve diagnostic accuracy, predict tumor resectability and response to therapy, ultimately leading to more effective personalized treatment strategies and improved patient outcomes. The development of robust and efficient AI-assisted tools holds significant promise for enhancing the speed and accuracy of diagnosis and treatment planning in this challenging disease.