Gallbladder Cancer Detection

Gallbladder cancer detection research focuses on improving the accuracy and efficiency of diagnosis using ultrasound (US) images and videos. Current efforts leverage deep learning models, including convolutional neural networks (CNNs), transformers, and masked autoencoders, often incorporating techniques like object detection and weakly supervised learning to address challenges posed by image quality and limited annotated data. These advancements aim to improve diagnostic accuracy, potentially surpassing human performance and enabling earlier, more effective intervention, ultimately impacting patient outcomes and healthcare resource allocation.