Fast GPU-beamforming of\\Row-Column Addressed Probe Data

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A delay-and-sum beamformer for 3D imaging using row-column arrays and written in CUDA is presented and compared to an existing similar GPU-based beamformer written in the MATLAB programming language. Data from a 192+192 rowcolumn array single element emission sequence is simulated and beamformed. The two beamformers’ performance is evaluated in two synthetic aperture setups comprised of 1) two orthogonal planes and 2) a full volume on three different NVIDIA GPUs: a 1050 Ti, a 1080 Ti, and a TITAN V. The execution time and the sample throughput (samples beamformed per second) are reported. The CUDA beamformer performs consistently better than the MATLAB beamformer with speed-ups ranging from 1.9 to 64.6 times, and the worst-case throughput of the CUDA beamformer exceeds the best-case of the MATLAB beamformer. High-resolution images of crossing planes can be beamformed at up to 13 Hz, while a 50-by-50-by-20 cubic-millimeter highresolution volume sampled at one quarter of a millimeter is beamformed in 3 seconds.
Original languageEnglish
Title of host publicationProceedings of 2019 IEEE International Ultrasonics Symposium
Number of pages4
Publication date2019
ISBN (Print)9781728145952
Publication statusPublished - 2019
Event2019 IEEE International Ultrasonics Symposium - SEC Glasgow, Glasgow, United Kingdom
Duration: 6 Oct 20199 Oct 2019


Conference2019 IEEE International Ultrasonics Symposium
LocationSEC Glasgow
CountryUnited Kingdom
Internet address

Cite this

Stuart, M. B., Jensen, P. M., Olsen, J. T. R., Kristensen, A. B., Schou, M., Dammann, B., Sørensen, H. H. B., & Jensen, J. A. (2019). Fast GPU-beamforming of\\Row-Column Addressed Probe Data. In Proceedings of 2019 IEEE International Ultrasonics Symposium (pp. 1497-1500). IEEE.