Suppression of Side Lobe Using Spectral Weights of Channel Data in Medical Ultrasonic Imaging System

In the receive focusing in an ultrasound imaging system, we calculate the magnitude of the main and side lobe spectrum of received channel data using a two-dimensional Fourier transform. During the ultrasound receive focusing process, if signals coming from outside the imaging point are not completely removed, side lobe occurs in the image. Because the time signal of the side lobe is difficult to distinguish from the time signal of the imaging point, it is hard to remove it using time domain filter processing. However, if the received channel-time data is transformed by a two-dimensional Fourier transform, the spectrum of the main lobe and side lobe can be separated in the spectral domain. Therefore, the magnitude of the main lobe and side lobe spectra and the distance between the centroid of the two spectra were used to design a time domain side lobe suppression filter weight. We suppress the side lobe by multiplying the ultrasound image by spectral weights. To assess the filter performance, ultrasound RF data from the human organs were synthesized on a computer at the 5 MHz and 64-channel linear array transducer. We compared the conventional focusing image, weights applied image, Hamming apodization image, and the main lobe only image. Computer simulations showed a significant increase in the contrast of the lesion while maintaining resolution.