Ultrasound Image Reconstruction

Ultrasound image reconstruction aims to create high-quality, three-dimensional images from raw ultrasound data, overcoming limitations of traditional methods like low resolution and artifacts. Current research focuses on leveraging deep learning, particularly neural networks (including neural radiance fields and Swin Transformers) and diffusion models, to improve reconstruction speed, accuracy, and robustness, often incorporating physics-based models for enhanced realism. These advancements are significant for improving medical diagnostics and interventional procedures by providing clearer, more detailed, and readily accessible 3D ultrasound images.