Conformador de imagen ultrasónica basado en redes neuronales

The current investigation delves into the capabilities of deep neural networks for configuring an ultrasonic beamformer with the ability to mitigate secondary lobe structures within images. Through experimentation with a collection of simulated signals, the results obtained underscore the feasibility of achieving this objective within a synthetic aperture imaging framework. Notably, data structure, improvements in lateral resolution are also demonstrated to be attainable..