Liver Tumor

Liver tumor research focuses on improving early diagnosis and precise classification of different liver cancers, particularly hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA), to optimize treatment strategies. Current research employs advanced machine learning techniques, including deep learning models like convolutional neural networks (CNNs) and vision transformers (ViTs), often integrated with multi-omics data analysis and advanced image processing methods such as contrastive learning and attention mechanisms, to enhance diagnostic accuracy and robustness. These efforts leverage diverse data sources, including multi-phase CT scans, MRI, and histopathological images, aiming to improve the speed and accuracy of diagnosis, ultimately impacting patient outcomes and informing personalized treatment plans. The development of robust and reliable AI-driven tools for liver tumor detection and classification is a significant area of focus, with ongoing efforts to address challenges such as data heterogeneity and limited labeled data.