Minimum variance beamformer applied to frequency components of the RF signal of the eye: Enhancing the image quality of curved interfaces

Minimum variance beamformer has high potential in improving image quality through an adaptive apodization weight optimization approach, but its impact is conventionally limited to lateral resolution enhancements. Recently, we reported a high range resolution technique that applies minimum variance beamformer to the frequency components of the RF signal after a delay-and-sum process. The technique has high performance in the improvement of the range resolution when a target has flat interfaces, such as a longitudinal section of an artery. In the present study, we report further advance of this technique to enhance image quality of a normal swine eye whose anatomy is marked by multiple layers of curved interfaces. The reference signal is acquired by the coherent integration of the echoes from isolated interfaces to take account of the attenuation and the interface shape. The proposed technique succeeded to offer a sharp rendering of the cornea boundaries of the swine eye, where the center frequency of the transmit ultrasound pulse was 12 MHz. Computationally, it required 5 seconds using a laptop PC with a single CPU for the depiction of an image in the ROI that consists of 422,528 pixels. We reckon that, if the proposed technique is implemented using GPUs, high-quality images of the eye (with both lateral and range resolution enhancements) can be readily achieved in real time.