Embedded GPU Implementation for High-Performance Ultrasound Imaging

Abstract

Methods of increasing complexity are currently being proposed for ultrasound (US) echographic signal processing. Graphics Processing Unit (GPU) resources allowing massive exploitation of parallel computing are ideal candidates for these tasks. Many high-performance US instruments, including open scanners like ULA-OP 256, have an architecture based only on Field-Programmable Gate Arrays (FPGAs) and/or Digital Signal Processors (DSPs). This paper proposes the implementation of the embedded NVIDIA Jetson Xavier AGX module on board ULA-OP 256. The system architecture was revised to allow the introduction of a new Peripheral Component Interconnect Express (PCIe) communication channel, while maintaining backward compatibility with all other embedded computing resources already on board. Moreover, the Input/Output (I/O) peripherals of the module make the ultrasound system independent, freeing the user from the need to use an external controlling PC.

The Design of an Efficient Low-Cost FPGA-based Unit for Generation Ultrasound Beamforming

“…The reception process by Rossi and Boni (2021) represents the process of data acquisition from the transducers; at its input, we find in generally DAC an analog-to-digital converter that samples the signals of the echoes acquired by the elements of the probe, then it converts these samples into digital information, considering the number of transducers to manage simultaneously, it is consistent, the management of different DAC is relegated to an FPGA board often more powerful than that one used in the pulser command generation. As mentioned earlier, the acquired data is processed using a DSP, a processor dedicated to signal processing, which the FPGA also manages.…”