Tumor Annotation

Tumor annotation in medical images focuses on accurately identifying and delineating tumor regions, crucial for diagnosis, treatment planning, and evaluating treatment response. Current research emphasizes developing efficient annotation methods, including weakly supervised learning techniques that leverage limited expert annotations alongside readily available clinical reports or image-level labels, often employing deep learning architectures like U-Net and variations of multiple instance learning. These advancements aim to reduce the substantial time and cost associated with manual annotation, ultimately improving the accuracy and accessibility of cancer diagnostics and research.