The feasibility of deep-learning algorithms integration on a GPU-based ultrasound research scanner

Ultrasound medical diagnostics is a real-time modality based on a doctor's interpretation of images. So far, automated Computer-Aided Diagnostic tools were not widely applied to ultrasound imaging. The emerging methods in Artificial Intelligence, namely deep-learning, gave rise to new applications in medical imaging modalities. The work's objective was to show the feasibility of implementing deep-learning algorithms directly on a research scanner with GPU software beamforming.