Ultrasound finds use in noninvasive imaging in cardiac, obstetric, gynecologic, and other diagnostic areas. What’s inside this tool that is playing an expanding role in today’s medical world?
The systems often operate in the 2- to 20-MHz frequency range. An ultrasound system transmits a phased array of sound waves through a linear transducer so that the waves constructively combine at a focal point. Transducers contain piezoelectric elements that are in sizes and shapes, such as linear or curved, to fit the application. As the generated sound waves propagate toward the focal point, they undergo a slight change in direction and produce a reflected sound wave each time they cross through matter of different densities. The linear transducer alternates between transmitting time-delayed sound pulses and receiving the reflection of these pulses as they pass through a region of interest. A variable controlled amplifier scales the reflected sound waves before an ADC samples and passes the data to the front-end processing of the system.
The front-end processing controls and performs beam-forming, which involves steering and focusing the phased array of sound waves. Steering involves sweeping the angle and direction of the beam to focal points with a precomputed depth. Focusing involves exciting multiple piezoelectric elements in the transducer with precisely time-delayed pulses so that the sound waves converge at each focal point along a scan line. When the sound waves reach the focal point, some of the sound reflects back toward the transducer as if the focal point were emitting the sound. The receiver’s beam-forming ability detects the time delay, phase, and amplitude of the reflected sound wave at each focal-point location to reconstruct the flight path of the waves using a delay and sum algorithm to support creating an ultrasound image.
The midprocessing end lacks a common definition, but it can include filter, detection, and compression processing on a scan line of beam-formed data. The filter processing is typically bandpass filtering to reduce noise and to select whether the imaging uses the fundamental frequency, as in conventional imaging, or the second harmonic, as in harmonic imaging. Conventional imaging has better penetration when detecting images deep in a human body; however, harmonic imaging supports better tissue-distinguishing resolution from-higher frequency operation.
The detection processing extracts a signal from the envelope of the signal. A complex rotator demodulates the signal in baseband; lowpass filtering then eliminate side lobes. This technique requires that the system must know and track the operating-center frequency. The system may perform additional lowpass filtering with decimation or interpolation before presenting this data for back-end processing. Another form of detection uses a Hilbert transform, an operation that is independent of the operating frequency but more complex than the rotator approach.
The back-end processing focuses on forming quality images for display from the received data. The type of processing and order of operation depend on the application and overall system configuration. Back-end processing can perform a variety of operations to ready an image for display. A scan conversion interpolates raw-data coordinates to displayed-data coordinates. The raw data can be in Cartesian coordinates for linear probes or polar coordinates for curvilinear or phased-array probes. Angle or spatial compounding uses multiple images to reduce "speckle"—a random intensity pattern produced by the mutual interference of a set of wave fronts—by combining views of the same object from different angles. Because the speckle in each view is uncorrelated, the resulting image can significantly reduce the amount of speckle. Frame-smoothing techniques reduce noise without blurring the image’s edges. Edge-detection techniques can help remove this blurring.
Doppler processing focuses on measuring and displaying shifts and motion of structures, such as blood flow, in the data. A CW (continuous-wave)-Doppler system is analog and is highly sensitive and selective so that it can estimate velocities. It is appropriate for spectral display, which continuously displays and updates data. To overcome the range ambiguity in CW-Doppler processing, a system can use a PW (pulsed-wave) Doppler, which sends known pulses to a target at a certain range. Doppler causes the received pulses to dilate or contract so that the delay in the arrival of the pulse provides velocity information.
Display-mode-dependent processing is vendor-specific and plays a critical role in producing images on the display. This type of processing can include look-up tables to convert echo amplitudes to display brightness or color to adjust for ambient lighting. This type of processing can involve the combination of simultaneous overlays, such as color Doppler and color-flow imaging. Display-mode-dependent processing can also include support for the user interface, including menus, help, and display options.
Block diagram courtesy Texas Instruments; images courtesy Zonare Medical Systems. For more information about ultrasound, see "Diagnostic ultrasound gets smaller, faster, and more useful," EDN, June 25, 2009, pg 21.
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