Implementing Capon beamforming on the GPU for real time cardiac ultrasound imaging

Recent work on Capon beamforming suggest that it can provide increased lateral resolution when applied in a medical ultrasound imaging setting. In this paper, the high computational complexity of the Capon beamformer is targeted with the use of a Graphics Processing Unit (GPU). In-vivo results with Capon beamforming applied on a full cardiac cycle in addition to simulations are presented. With the GPU we are able to process a 70° sector cardiac image from a 64 element phased array at interactive frame rates using both spatial and temporal smoothing. For a typical cardiac ultrasound image of 80 × 400 pixels (70° sector, 15 cm range) acquired using a 2.5 MHz, M=64 element phased array, we obtain 10 fps (subarray length L=M/2, temporal smoothing over 3 samples). If we perform a 2-element pre-beamforming, the channel count is reduced to 32, and frame rate is increased to 44 fps. For a 32 element phased array we need less beams to cover the sector (40 × 400 pixels), hence with the same parameters the frame rate increases to 87 fps. The target GPU was the Nvidias Quadro 6000, capable of 1 Tflops.