Artificial-Intelligence-Enhanced Ultrasound Flow Imaging at the Edge

Ultrasound flow imaging has long been used for cardiovascular diagnostics. Color Doppler imaging (CDI) is the predominant ultrasound flow imaging mode, but its diagnostic value is hampered by aliasing artifacts that limit the range of detectable blood velocities. Here, we present the first demonstration of how edge artificial intelligence (AI) can enable real-time CDI with aliasing resistance. Specifically, graphical processing unit acceleration and AI-ready edge computing hardware have been leveraged to realize the first end-to-end CDI processing pipeline that involves AI-based aliasing correction. Performance results show that, using our edge AI engine, aliasing-resistant CDI frames with threefold velocity detection range can be generated at a real-time frame rate of 25 frames per second (for raw datasets with 192 channels, 12-bit data resolution, and 25-MHz sampling rate). Overall, edge AI can critically improve the real-time visualization quality of ultrasound flow imaging and, in turn, potentially transform its bedside application value.