Ultrasound Image Analysis

Ultrasound image analysis focuses on developing automated methods to extract meaningful information from ultrasound scans, improving diagnostic accuracy and efficiency. Current research heavily utilizes deep learning, employing architectures like convolutional neural networks (CNNs), generative adversarial networks (GANs), and U-Nets, often combined with multimodal data fusion strategies to overcome challenges like image noise and limited training data. These advancements are impacting various medical fields, enabling faster and more precise diagnoses, particularly in fetal assessment, cancer detection, and the assessment of lung conditions like pneumonia, ultimately improving patient care.