Phase Aberration

Phase aberration, caused by variations in sound speed within imaging media, degrades image quality in ultrasound by disrupting wave propagation and coherent signal summation. Current research focuses on developing deep learning-based methods, particularly convolutional neural networks (CNNs), to correct for these aberrations, often employing self-supervised or adaptive loss function strategies that avoid the need for reference data. These advancements aim to improve the accuracy and diagnostic capabilities of ultrasound imaging, particularly in challenging deep tissue scans, by mitigating artifacts caused by phase aberration.