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Frequency domain beamforming in ultrasound imaging (Technion)

Most ultrasound imaging systems use multiple transducer elements to transmit and receive acoustic pulses. Beamforming of the signals detected by the individual elements of the array increase the signal-to-noise ratio and angular resolution, while performance in the digital domain, implies that the analog signals detected at the receiver elements are sampled first. The required sampling rates result in a considerable amount of data to store and process. Reduction of processing rates is possible within the classical sampling framework by exploiting the fact that the signal is modulated onto a carrier and occupies only a portion of its entire baseband bandwidth. When data is down-sampled digitally at the system front-end, the sampling rate remains unchanged, hence only the processing rate is reduced, implying that only a partial solution is achieved. Other recently developed techniques reduce the number of samples needed to reconstruct the image comprised of strong reflectors, but this approach treats only the strong reflections in the signal and is not able to capture a speckle pattern, which is of high importance in medical imaging.The presented method allows the translation of beamforming to the Fourier domain. This enables the use of the low bandwidth of ultrasound signals and allows to compute the beamformed signal directly in frequency using Fourier coefficients of the individual detected signals. The required set of individual signals' Fourier coefficients is calculated from a small number of their low-rate samples. Exploiting the low bandwidth of the beamformed signal allows us to obtain the same beamformed image as in standard beamforming but from far fewer samples. The reconstruction process is very simple and can be performed using the highly effective Fast Fourier Transform algorithm. It can also be applied at sub-Nyquist levels when the signal's structure is exploited and novel compressed sensing algorithms are used for signal reconstruction. This leads to further rate reduction, while retaining sufficient image quality.
Technology Benefits
• Reduces the signal sampling up to 16 fold and lowers the processing rates without compromising quality
• Able to perform beamforming from a much smaller number of samples, with lower memory and computational requirements
• Applicable at sub-Nyquist levels
Technology Application
• Narrowband based techniques such as sonar
• Companies manufacturing medical imaging equipment
• Medical and nondestructive testing applications
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