AI-based CT Image Segmentation and Classification Methods for COVID-19 Inspection

Research on AI-based CT image segmentation and classification for COVID-19 primarily focuses on developing and refining algorithms that can accurately identify and differentiate COVID-19 features from CT scans. These studies leverage deep learning models, particularly convolutional neural networks (CNNs), to automate the detection and assessment of COVID-19-related anomalies in lung tissues. A key comparison in this domain highlights the use of various architectures like U-Net for segmentation and ResNet for classification, which show significant efficacy in enhancing diagnostic speed and accuracy.