Ultrafast Plane Wave Imaging Using Tensor Completion-Based Minimum Variance Algorithm.

Abstract

Coherent plane wave compounding (CPWC) imaging is an efficient technique in high-frame-rate ultrasound imaging. To improve the image quality obtained from the CPWC, the adaptive minimum variance (MV) algorithm can be used. However, the high computational complexity of this algorithm negatively affects the frame rate. In other words, achieving a high frame rate and high-quality features simultaneously remains a challenge in medical ultrasound imaging. The aim of the work described here was to develop an algorithm to tackle this challenge and improve the frame rate while preserving the good quality of the resulting image. A tensor completion (TC)-based MV algorithm is proposed to simultaneously improve the frame rate and image quality in CPWC. In the proposed method, the MV algorithm is applied to a limited number of pixels in the beamforming grid. Then, the appropriate values are assigned to the remaining unprocessed pixels by using the TC algorithm. The proposed algorithm speeds up the beamforming process, and consequently, improves the frame rate. The computational complexity of the proposed TC-based MV algorithm is reduced compared with that of the conventional MV algorithm while the good quality of this algorithm is preserved. The results indicate that, in particular, by processing 40% of the beamforming grid using the MV beamformer followed by the TC algorithm, a reconstructed image comparable to that in the case in which the MV algorithm is performed on the full beamforming grid is obtained; the difference between the contrast-to-noise ratio evaluation metric between these two cases is about 0.16 dB for the experimental-resolution phantom. Also, the resulting images obtained from the MV algorithm and the TC-based MV method have the same resolution, indicating that the TC-based MV algorithm can successfully achieve the quality of the MV algorithm with a lower computational complexity. The TC-based MV algorithm is proposed in CPWC with the goal of improving frame rate and image quality. Qualitative and quantitative results reveal that by use of the proposed algorithm, the quality of the reconstructed image will be comparable to that of the conventional MV algorithm, and the frame rate will be improved.