A Real-Time, GPU-Based Implementation of Aperture Domain Model Image REconstruction

Multipath and off-axis scattering are two of the primary mechanisms for ultrasound image degradation. To address their impact, we have proposed Aperture Domain Model Image REconstruction (ADMIRE). This algorithm utilizes a model-based approach in order to identify and suppress sources of acoustic clutter. The ability of ADMIRE to suppress clutter and improve image quality has been demonstrated in previous works, but its use for real-time imaging has been infeasible due to its significant computational requirements. However, in recent years, the use of graphics processing units (GPUs) for general-purpose computing has enabled the significant acceleration of compute-intensive algorithms. This is because many modern GPUs have thousands of computational cores that can be utilized to perform massively parallel processing. Therefore, in this work, we have developed a GPU-based implementation of ADMIRE. The implementation on a single GPU provides a speedup of two orders of magnitude when compared to a serial CPU implementation, and additional speedup is achieved when the computations are distributed across two GPUs. In addition, we demonstrate the feasibility of the GPU implementation to be used for real-time imaging by interfacing it with a Verasonics Vantage 128 ultrasound research system. Moreover, we show that other beamforming techniques, such as delay-and-sum (DAS) and short-lag spatial coherence (SLSC), can be computed and simultaneously displayed with ADMIRE. The frame rate depends upon various parameters, and this is exhibited in the multiple imaging cases that are presented. An open-source code repository containing CPU and GPU implementations of ADMIRE is also provided.