Toward parallel optimal computation of ultrasound computed tomography using GPU

Abstract

In recent years, many research studies have been carried out on ultrasound computed tomography (USCT) for its application prospect in early detection of breast cancer. The synthetic aperture focusing technique (SAFT) widely used for the USCT image reconstruction is highly compute-intensive. Speeding up and optimizing the reconstruction algorithm on the graphics processing units (GPUs) have been highly applied to medical ultrasound imaging field. In this paper, we focus on accelerating the processing speed of SAFT with the GPU, considering its high parallel computation ability. The main computational features of SAFT are discussed to show the degree of computation parallelism. On the basis of the compute unified device architecture (CUDA) programming model and the Single Instruction Multiple Threads (SIMT) model, the optimization of SAFT parallel computation is performed. The proposed method was verified with the radio-frequency (RF) data of the breast phantom and the pig heart in vitro captured by the USCT system developed in the Medical Ultrasound Laboratory. Experimental results show that a 1024×1024 image reconstruction with a single NVIDIA GTX-1050 GPU could be 25 times faster than that with a 3.20-GHz Intel Core-i5 processor without image quality loss. The results also imply that with the increase of the image pixels, the acceleration effect is more notable.