Mediastinal Lymph Node

Mediastinal lymph node analysis is crucial for cancer staging and treatment planning, focusing on accurate detection and quantification from medical images like CT scans. Current research heavily emphasizes the development and refinement of deep learning models, including variations of UNet and Swin Transformer architectures, often employing weakly supervised or semi-supervised learning techniques to address the scarcity of fully annotated datasets. These advancements aim to improve the speed and accuracy of lymph node identification, ultimately leading to more precise cancer diagnosis and personalized treatment strategies. The ongoing challenge lies in balancing the need for high-quality annotations with the development of robust algorithms capable of handling incomplete or noisy data.