Various methods are used in ultrasound beamforming to increase signal-to-noise ratio (SNR) and improve
spatial resolution. SNR is typically improved by exploiting coherence in the RF channel data, for example summing
channel data after applying focal delays in the delay-and-sum (DAS) beamformer, and summing channel data after
applying a per-channel matched filter for the spatial matched filter beamformer. Inverse filter methods are
capable of improving spatial resolution at the cost of SNR ,, or can trade resolution for SNR using a
regularization parameter, but in general are very computationally intensive due to the large RF data sets used. We
propose a post-processing method operating on post-summed but pre-envelope detected beamformed image data
that can improve the pixel SNR and spatial resolution of any beamformer with low computational cost. This is
achieved by forming a new pixel for each point in the image as a linear combination of the surrounding
beamformed pixels. The weights for each pixel are calculated in advance using a quadratically constrained least
squares method to reduce PSF energy outside the mainlobe and noise energy. Simulations indicate that this method
can increase cystic contrast by up to 20dB without any cost in SNR, and can increase pixel SNR can by up 16dB
without affecting contrast. Alternatively, simultaneous gains in contrast and SNR can be achieved. Experimental
results show smaller performance improvements yet validate the feasibility of this technique.
Medical Ultrasound Imaging is widely used clinically because of its relatively low cost, portability, lack of
ionizing radiation, and real-time nature. However, even with these advantages ultrasound has failed to
permeate the broad array of clinical applications where its use could be of value. A prime example of this untapped potential is the routine use of ultrasound to guide intravenous access. In this particular application existing systems lack the required portability, low cost, and ease-of-use required for widespread acceptance.
Our team has been working for a number of years to develop an extremely low-cost, pocket-sized, and
intuitive ultrasound imaging system that we refer to as the "Sonic Window." We have previously described
the first generation Sonic Window prototype that was a bench-top device using a 1024 element, fully
populated array operating at a center frequency of 3.3 MHz. Through a high degree of custom front-end
integration combined with multiplexing down to a 2 channel PC based digitizer this system acquired a full
set of RF data over a course of 512 transmit events. While initial results were encouraging, this system
exhibited limitations resulting from low SNR, relatively coarse array sampling, and relatively slow data acquisition.
We have recently begun assembling a second-generation Sonic Window system. This system uses a 3600 element fully sampled array operating at 5.0 MHz with a 300 micron element pitch. This system extends the
integration of the first generation system to include front-end protection, pre-amplification, a programmable
bandpass filter, four sample and holds, and four A/D converters for all 3600 channels in a set of custom
integrated circuits with a combined area smaller than the 1.8 x 1.8 cm footprint of the transducer array. We
present initial results from this front-end and present benchmark results from a software beamformer
implemented on the Analog Devices BF-561 DSP. We discuss our immediate plans for further integration
and testing. This second prototype represents a major reduction in size and forms the foundation of a fully
functional, fully integrated, pocket sized prototype.