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https://doi.org/10.3938/NPSM.67.106
GPU-Accelerated Signal Processing of Beam Formation and Envelope Detection for Real-Time Ultrasound Imaging
New Physics: Sae Mulli 2017; 67: 106~112
Published online January 31, 2017;  https://doi.org/10.3938/NPSM.67.106
© 2017 New Physics: Sae Mulli.

Wonji LEE1, Myunggi YI*2

1 Department of Biomedical Engineering, Pukyong National University, Busan 48513, Korea
2 Interdisciplinary Program of Biomedical, Mechaincal and Electrical Engineering, Department of Biomedical Engineering, Pukyong National University, Busan 48513, Korea
Correspondence to: myunggi@pknu.ac.kr
Received August 29, 2016; Revised October 18, 2016; Accepted October 19, 2016.
cc This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
High-speed signal processing is essential for real-time displays in medical imaging applications. Photoacoustic tomography provides structural, functional, and molecular imaging with high resolution in a noninvasive way. Especially, three-dimensional image reconstruction, functional imaging, and real-time display require fast signal processing. Here, we provide a high-speed signal processing method using a graphic processing unit (GPU) to reconstruct ultrasound or photoacoustic B-mode images for real-time displays. The signal processing speed was improved by parallel processing of the beam formation and the envelop detection required for image reconstruction using a massive number of GPU cores. The time using a GPU was 2.778 ms, on average, to process a single-frame B-mode image with 128 $\times$ 3200 pixels while it was about 3.165 seconds using a central processing unit (CPU). The processing time using a GPU was short enough to reconstruct three-dimensional images for real-time displays.
PACS numbers: 87.85.Ng
Keywords: GPU-accelerated signal processing, Ultrasound imaging, Photoacoustic imaging, Real-time display, Parallel computing


July 2017, 67 (7)