Ultrasound systems are among the most advanced signal processing instruments currently in wide use. As with any complex device, achieving optimal performance involves a series of trade-offs influenced by factors such as performance requirements, physical constraints, and cost. To fully grasp the functionality and performance of key front-end integrated circuits (ICs), such as low-noise amplifiers (LNAs), time gain compensation amplifiers (TGCs), and analog-to-digital converters (ADCs), it is essential to have a solid understanding of system-level design. These analog components play a critical role in determining the overall system performance. Once noise or distortion is introduced at the front end, it becomes nearly impossible to eliminate later in the signal chain.
In all ultrasound systems, a multi-sensor array is connected via a long cable (typically around 2 meters) containing between 48 to 256 micro-coaxial cables. Some systems use high-voltage multiplexers or demultiplexers to reduce hardware complexity during transmission and reception, but this often comes at the cost of reduced flexibility. Phased array digital beamformer systems offer the highest level of flexibility, as they allow full electronic control of all channels. However, these systems tend to be more expensive due to the complexity involved. Fortunately, modern front-end ICs like the AD8332 dual VGA, AD8335 quad VGA, and AD9229 12-bit quad ADC are helping to reduce costs and power consumption per channel, making full electronic control more accessible even in lower-cost systems.
At the transmit (Tx) side, the Tx beamformer determines the delay pattern needed to achieve the desired focus, and then the signal is amplified by a high-voltage amplifier that drives the transducer. On the receive (Rx) side, a T/R switch — usually a diode rectifier bridge — isolates the high-voltage Tx pulses before the signal passes through an LNA and one or more VGAs for further amplification.
**Figure 1: Basic block diagram of the DBF system**
After amplification, either analog beamforming (ABF) or digital beamforming (DBF) is performed. In addition to continuous wave (CW) Doppler processing, the dynamic range of received signals is too large to be handled by imaging channels alone, which is why most modern systems rely on DBF. The final processed Rx beam is used to generate grayscale images, two-dimensional color images, and/or color Doppler outputs.
The primary goal of an ultrasound system is to produce accurate internal organ images and to assess blood flow movement using Doppler signal processing. This requires overcoming several technical challenges, including signal attenuation, power consumption, and managing a large dynamic range. Choosing the right front-end ICs is crucial in addressing these challenges effectively.
**1. Signal Attenuation Problem**
Medical ultrasound operates across a wide frequency range, typically from 1 MHz to 40 MHz. External imaging usually uses frequencies between 1 MHz and 15 MHz, while venous imaging may go up to 40 MHz. For a given depth, higher-frequency signals experience greater tissue attenuation. Specifically, the signal loss is approximately 1 dB/cm/MHz. For example, a 10 MHz signal traveling 5 cm into tissue would suffer a round-trip attenuation of about 100 dB.
This presents a major challenge for the receiver, which must handle both very weak and very strong signals. The receiving circuit needs to maintain low noise levels while also having the capability to process large signals. Additionally, fast overload recovery is essential. Even the T/R switch can cause issues if a small portion of the transmitted pulse leaks through and overloads the receiver. If the receiver cannot recover quickly, it may become "blind" for a short period, directly affecting the quality of the image near the skin surface.
**2. ABF and DBF Systems**
In analog ABF and digital DBF ultrasound systems, the signals from each channel are delayed or stored based on the focal point along the beam. They are then time-ordered and coherently summed, providing spatial processing gain due to the correlation of the signal and the uncorrelated nature of the noise. This results in a theoretical gain of 10 log(N), where N is the number of channels.
There are two main ways to form images: in ABF, analog values are simulated using delay lines, summed, and then converted to digital values after summation. In DBF, the analog signals from the array elements are sampled, stored in memory (FIFO), and then digitally summed. The figure shows a basic DBF system, where ADCs and FIFOs replace variable delay lines used in ABF systems.
Both systems require excellent channel-to-channel matching. While both need VGAs, ABF systems only require a high-resolution, relatively low-speed ADC after signal summation, whereas DBF systems demand multiple high-speed, high-resolution ADCs to capture RF bandpass signals directly.
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