Photoacoustic Imaging

Photoacoustic imaging (PAI) is a hybrid imaging modality combining optical contrast with ultrasound detection to create high-resolution images of biological tissues. Current research focuses on improving image reconstruction, particularly from limited-view or sparse data, using deep learning techniques such as neural networks (including U-Nets, EfficientNets, and transformers), and novel algorithms like differentiable rendering and diffusion models to overcome challenges posed by speed of sound heterogeneity and limited sensor coverage. These advancements are significantly improving image quality and speed, leading to potential applications in diverse fields including medical diagnostics and preclinical research, particularly in areas like cancer detection and monitoring.