Beam-domain eigenspace-based minimum variance beamformer for medical ultrasound imaging

The eigenspace-based minimum variance (ESBMV) beamformer can provide good imaging resolution and contrast; however, the performance is achieved at the cost of high computational complexity. In adaptive array processing, the beamspace method is an efficient way to lower the computational complexity. In this paper, we combine the beamspace method with the ESBMV beamformer and propose a beamdomain ESBMV beamformer. We demonstrate the feasibility of introducing the beamspace into the ESBMV beamformer and propose an effective method of forming the transform matrix based on the spatial spectrum of the array signals. We also illustrate the performance of the proposed beamformer when resolving point scatterers and a cyst phantom with both simulated and experimental data. The results show that the proposed method can achieve performance comparable to the ESBMV beamformer within much shorter time.