B Mode

B-mode ultrasound imaging, a cornerstone of medical diagnostics, is undergoing significant advancements driven by machine learning. Current research focuses on improving image quality and analysis through techniques like deep learning (including convolutional neural networks and transformers), self-supervised learning leveraging intra-video image pairs, and novel signal processing methods such as Nakagami imaging for enhanced tissue characterization. These improvements aim to increase the accuracy and efficiency of diagnoses across various applications, from detecting hip dysplasia in infants to identifying prostate cancer and assessing cardiac function, ultimately leading to better patient care and more accessible diagnostic tools.