Infection Segmentation

Infection segmentation in medical imaging, primarily using chest CT scans, aims to automatically identify and delineate infected regions within the lungs, facilitating faster and more accurate diagnosis. Current research focuses on developing robust deep learning models, including convolutional neural networks (CNNs) with multi-scale architectures and semi-supervised learning techniques to address data scarcity issues, often employing strategies like mean teacher networks or generative models to synthesize additional training data. These advancements are crucial for improving the efficiency and objectivity of disease diagnosis, particularly in scenarios like COVID-19 outbreaks where rapid and accurate assessment is critical.