Lung Window

Lung windowing, a technique adjusting the display range of computed tomography (CT) images to highlight lung tissue, is crucial for accurate diagnosis and analysis, particularly in applications like detecting chronic obstructive pulmonary disease (COPD). Current research focuses on automating this process, employing convolutional neural networks (CNNs), particularly DenseNet architectures, and exploring the integration of mediastinal window information to improve diagnostic accuracy. These advancements aim to reduce the workload associated with manual image analysis, leading to faster, more efficient, and potentially more accurate diagnoses in various cardiac and pulmonary applications.