Lung CT

Lung CT image analysis is a rapidly evolving field focused on improving the accuracy and efficiency of diagnosing and monitoring lung diseases. Current research emphasizes the development of advanced deep learning models, including convolutional neural networks (CNNs), Vision Transformers, and normalizing flows, often incorporating techniques like attention mechanisms and multi-scale feature extraction to address challenges such as detecting small nodules and segmenting complex lung pathologies. These advancements are significantly impacting clinical practice by enabling faster, more accurate diagnoses, particularly for conditions like lung cancer and COVID-19, and facilitating improved treatment planning and monitoring. Furthermore, active learning and data augmentation strategies are being explored to reduce annotation costs and improve model robustness.