Models · Hugging Face
Adaptive Ultrasound Imaging with Physics-Informed NV-Raw2Insights-US AI
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Ultrasound is one of the most widely used medical imaging modalities due to its safety, real-time capability, portability, and low cost.
Key facts
- An Altera Agilex-7 FPGA development kit paired with NVIDIA Holoscan Sensor Bridge enables raw ultrasound channel data streaming from an ACUSON Sequoia ultrasound scanner’s DisplayPort outputs
- Holoscan Sensor Bridge (HSB), is an open source FPGA IP developed by NVIDIA that allows high-bandwidth low latency data transfer to the GPU via ( RDMA over Converged Ethernet)
- This project was conducted in close collaboration with Siemens-Healthineers, they are appreciative of their support, including the direct collaboration of Ismayil Guracar and Rickard Loftman of the AI
- The NVIDIA HSB then packetizes the data and transmits it over Ethernet to NVIDIA IGX for data collection and AI inference
Summary
In the era of AI and foundation models, a natural question emerges: can they move beyond the traditional beamforming pipeline, learn directly from raw ultrasound sensor data, and make use of information that is normally discarded during reconstruction? NVIDIA and researchers from Siemens Healthineers teamed up to find answers to these questions. At its core, ultrasound is not an image—it’s sound. Their approach starts earlier. Instead of working from finished images, NV-Raw2Insights-US learns directly from the raw signals captured by the ultrasound probe—the closest representation of how sound truly interacts with the body.