An ultrasound image is formed from a collection of ultrasonic beams transmitted and received by an array of transducer elements.  As the resolution of an image and the range over which an image is to be formed increase, so do the number of these transducer elements and the corresponding digital processing units.  The intensive signal processing power required for ultrasound imaging ^[1] means that conventional ultrasound systems are often large and expensive, and this demand for processing power can only worsen as more transducers and signal channels are implemented.  In applications such as point-of-care diagnostics in rural areas, the movement to a portable and low-power ultrasound imaging system is warranted.

Beamforming, which in its simplest form involves delaying, scaling, and summing to produce a coherent signal from the collection of received beams, has been identified as an area for algorithmic research and development ^[2] .  In this work, an 8-channel wide, scalable digital beamformer is implemented with feedback for power reduction.  Two modes of operation are available: coarse and fine beamforming.  In the coarse beamforming mode, digitized data from an evenly spaced subset of transducer elements are processed, providing a low-quality image of the full region of interest, which yields power savings by turning off the analog front end electronics and analog-to-digital converters corresponding to the unused 50% or 75% of array channels (schematically shown in Figure 1).  Figures 2a and b show the coarse images for quarter and half resolution coarse beamforming modes.  Next, the user can specify a smaller region in which a higher quality image is desired, which is then beamformed by the same 8-channel wide processing unit using all available channels (an example of the full region full resolution image is shown in Figure 2c).

1. M. Ali, D. Magee, and U. Dasgupta, “Signal processing overview of ultrasound systems for medical imaging,” Texas Instruments, Dallas, TX, SPRAB12, 2008.
2. S. Stergiopoulos, Advanced Signal Processing Handbook: Theory and Implementation for Radar, Sonar, and Medical Imaging Real-Time Systems.  Boca Raton: CRC Press, Inc., 2000.

The Capacitive Micromachined Ultrasound Transducer (CMUT) is an alternative to traditional piezoelectric transducers. The CMUT technology provides an opportunity for highly integrated ultrasound-imaging system solutions because of its CMOS compatibility and ease of large array fabrication ^[1] .

This project aims to provide a highly flexible platform for 3D ultrasound imaging. Figure 1 presents the system architecture. The CMUT device is flip-chip bonded to the supporting electronic circuits, which eliminates the cables. As a result, the channel count of the imaging system is increased and the capacitive loading due to cables is greatly reduced. The transmitters in the system are reconfigurable to implement Tx Beamforming; the analog front-end receivers and the DSP perform various Rx Beamforming algorithms from the received echo waveforms. We successfully implemented a 2D ultrasound imaging system based on a 1D transducer and corresponding electronics as the first step. Currently a 3D ultrasound-imaging system using 2D transducers is investigated.

In the finished 1D IC fabricated in 0.18µm CMOS process, we implemented 4 channels of Tx and Rx analog front-end circuits. Each channel includes an LNA, a VGA and a high voltage pulser. Acoustic measurements are carried out to demonstrate the improved energy efficiency of the 3-level pulser in Tx. A mechanical 3D translation stage is set up, which mounts a hydrophone to probe ultrasound pressure in the medium. The pressure field measured is referred back to the surface of the CMUT transducer, so that the total emitted acoustic power can be calculated. The Tx efficiency is measured by dividing the acoustic power by the total transmission power. Different pulse shapes lead to different Tx efficiency results. The efficiency improvement of 3-level pulse shape over the traditional 2-level pulse shape is measured to be approximately 50%, which is in agreement with the theory (shown in Figure 2).

1. O. Oralkan, “Acoustical imaging using capacitive micromachined ultrasonic transducer arrays: Devices, circuits, and systems,” Ph.D. dissertation, Stanford, Palo Alto, 2004.