Applying the Chirp Scaling Algorithm for Efficient Beamforming of Ultrasound Images.

To produce high-resolution ultrasound images, synthetic aperture acquisitions are used, which contain a large amount of data that is difficult to beamform in real time with traditional methods like delay and sum (DAS). Although frequency domain beamforming methods have been adapted to ultrasound, the existing adaptations require interpolation. The chirp scaling algorithm (CSA), which was originally developed for radar remote sensing applications, avoids interpolation by using the Fourier transform shift property, so modifying CSA for ultrasound could expedite computation while avoiding interpolation error, improving rapid image formation. This work adapts CSA theory for typical monostatic ultrasound acquisitions and tests the algorithm on point target and lesion simulations to analyze image quality and computational speed. While CSA achieves similar image quality as related frequency domain beamformers (such as the range-Doppler algorithm - RDA), its runtime is lower than both DAS and RDA. With further adaptations, the algorithm could benefit real-time, high-resolution clinical imaging.