Performance Assessment of Side Lobe Suppression Filters Based on Ground Truth Ultrasound Image

When echoes are focused to obtain an ultrasound image, the point spread function of a sound field calculated by using the ray tracing method consists of a main lobe echo from the imaging point and a side lobe echo from outside the imaging point. If the position of all the scatterers in an imaging area is known, the propagation path of ultrasound can be calculated, and the main and side lobe echoes can be separated in the beamforming computation. We converted the gray level of an MR image of a human organ into an ultrasonic reflectivity distribution from the knowledge of the reflectivity and position of all the scatterers inside an organ of the human body and used to form an ultrasound image. Using computer simulation, we constructed the main lobe, side lobe, and conventional images by separating in image forming process echo signals due to the main and side lobes. The main lobe image can be considered as an ideal ground truth image that can be used to assess the performance of signal processing methods applied to a conventional image. We estimated side lobes from a conventional ultrasound image and designed side lobe suppression filters based on them. We applied the minimum variance beamforming and three types of side lobe suppression filters to a conventional ultrasound image, and compared the resulting image with the main lobe image. Although the proposed method cannot be applied to in vivo ultrasound data acquired from the human body, it can be applied to synthesized data converted from images of other imaging modalities, thereby making more realistic comparison possible than with phantom data. Our method may be used as a quantitative method for evaluating the performance of focusing in a medical ultrasound imaging system.