Digital Signal Processing Methodologies for Conventional Digital Medical Ultrasound Imaging System

Ultrasound imaging is an efficient, noninvasive, method for medical diagnosis. A commonly used approach to image acquisition in ultrasound system is digital beamforming. Digital beamforming, as applied to the medical ultrasound, is defined as phase alignment and summation of signals that are generated from a common source, by received at different times by a multi-elements ultrasound transducer. In this paper first: we tested all signal processing methodologies for digital beamforming which included: the effect of over sampling techniques, single trans mit focusing and their limitations, the apodization technique and its effect to reduce the sidelobes, the analytical envelope detection using digital finite impulse response (FIR) filter approximations for the Hilbert transformat ion and how to compress the dynamic range to achieve the desired dynamic range for display (8 bits). Here the image was reconstructed using physical array elements and virtual array elements for linear and phase array probe. The results shown that virtual array elements were given well results in linear array image reconstruction than physical array elements, because it provides additional number of lines. However, physical array elements shown a good results in linear phase array reconstruction (steering) than virtual array elements, because the active elements number (Aperture) is less than in physical array elements. We checked the quality of the image using quantitative entropy. Second: a modular FPGA-based 16 channel digital u ltrasound beamforming with embedded DSP for ultrasound imaging is presented. The system is implemented in Virtex-5 FPGA (Xilinx, Inc.). The system consists of: two 8 channels block, the DSP which composed of the FIR Hilbert filter b lock to obtain the quadrature components, the fractional delay filter block (in-phase filter) to compensate the delay when we were used a high FIR order, and the envelope detection block to compute the envelope of the in-phase and quadrature components. The Hilbert filter is implemented in the form whereby the zero tap coefficients were not computed and therefore an order L filter used only L/2 multiplications. This reduced the computational time by a half. From the implementation result the total estimated power consumption equals 4732.87 mW and the device utilization was acceptable. It is possible for the system to accept other devices for further processing. Also it is possible to build 16-,32-, and 64-channel beamformer. The hardware architecture of the design provided flexib ility for beamforming.