GPU-accelerated Double-stage Delay-multiply-and-sum Algorithm for Fast Photoacoustic Tomography Using LED Excitation and Linear Arrays

Seyyed Reza Miri Rostami; Moein Mozaffarzadeh; Mohsen Ghaffari-Miab; Ali Hariri; Jesse Jokerst

doi:10.1177/0161734619862488

GPU-accelerated Double-stage Delay-multiply-and-sum Algorithm for Fast Photoacoustic Tomography Using LED Excitation and Linear Arrays

Ultrason Imaging. 2019 Sep;41(5):301-316. doi: 10.1177/0161734619862488. Epub 2019 Jul 19.

Authors

Seyyed Reza Miri Rostami¹, Moein Mozaffarzadeh², Mohsen Ghaffari-Miab¹, Ali Hariri³, Jesse Jokerst^{3

4

5}

Affiliations

¹ 1 Computational Electromagnetics Laboratory, Department of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran.
² 2 Laboratory of Acoustical Wavefield Imaging, Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands.
³ 3 Department of NanoEngineering, University of California, San Diego, La Jolla, CA, USA.
⁴ 4 Materials Science and Engineering Program, University of California, San Diego, La Jolla, CA, USA.
⁵ 5 Department of Radiology, University of California, San Diego, La Jolla, CA, USA.

PMID: 31322057
DOI: 10.1177/0161734619862488

Abstract

Double-stage delay-multiply-and-sum (DS-DMAS) is an algorithm proposed for photoacoustic image reconstruction. The DS-DMAS algorithm offers a higher contrast than conventional delay-and-sum and delay-multiply and-sum but at the expense of higher computational complexity. Here, we utilized a compute unified device architecture (CUDA) graphics processing unit (GPU) parallel computation approach to address the high complexity of the DS-DMAS for photoacoustic image reconstruction generated from a commercial light-emitting diode (LED)-based photoacoustic scanner. In comparison with a single-threaded central processing unit (CPU), the GPU approach increased speeds by nearly 140-fold for 1024 × 1024 pixel image; there was no decrease in accuracy. The proposed implementation makes it possible to reconstruct photoacoustic images with frame rates of 250, 125, and 83.3 when the images are 64 × 64, 128 × 128, and 256 × 256, respectively. Thus, DS-DMAS can be efficiently used in clinical devices when coupled with CUDA GPU parallel computation.

Keywords: beamforming; central processing unit (CPU); compute unified device architecture (CUDA); double-stage delay-multiply-and-sum (DS-DMAS); graphics processing unit (GPU); linear-array imaging; parallel computing; photoacoustic imaging.

MeSH terms

Algorithms*
Computer Graphics*
Equipment Design
Image Processing, Computer-Assisted / methods*
Phantoms, Imaging
Photoacoustic Techniques / instrumentation
Photoacoustic Techniques / methods*
Signal Processing, Computer-Assisted*
Signal-To-Noise Ratio
Tomography