Literature DB >> 31322057

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

Seyyed Reza Miri Rostami1, Moein Mozaffarzadeh2, Mohsen Ghaffari-Miab1, Ali Hariri3, Jesse Jokerst3,4,5.   

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.

Entities:  

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

Year:  2019        PMID: 31322057     DOI: 10.1177/0161734619862488

Source DB:  PubMed          Journal:  Ultrason Imaging        ISSN: 0161-7346            Impact factor:   1.578


  8 in total

1.  Multi-angle data acquisition to compensate transducer finite size in photoacoustic tomography.

Authors:  Soheil Hakakzadeh; Moein Mozaffarzadeh; Seyed Masood Mostafavi; Zahra Kavehvash; Praveenbalaji Rajendran; Martin Verweij; Nico de Jong; Manojit Pramanik
Journal:  Photoacoustics       Date:  2022-05-21

2.  GPU implementation of photoacoustic short-lag spatial coherence imaging for improved image-guided interventions.

Authors:  Eduardo A Gonzalez; Muyinatu A Lediju Bell
Journal:  J Biomed Opt       Date:  2020-07       Impact factor: 3.170

3.  Optimizing Irradiation Geometry in LED-Based Photoacoustic Imaging with 3D Printed Flexible and Modular Light Delivery System.

Authors:  Maju Kuriakose; Christopher D Nguyen; Mithun Kuniyil Ajith Singh; Srivalleesha Mallidi
Journal:  Sensors (Basel)       Date:  2020-07-06       Impact factor: 3.576

4.  Enhanced contrast acoustic-resolution photoacoustic microscopy using double-stage delay-multiply-and-sum beamformer for vasculature imaging.

Authors:  Moein Mozaffarzadeh; Mehdi H H Varnosfaderani; Arunima Sharma; Manojit Pramanik; Nico de Jong; Martin D Verweij
Journal:  J Biophotonics       Date:  2019-08-07       Impact factor: 3.207

Review 5.  Achieving depth-independent lateral resolution in AR-PAM using the synthetic-aperture focusing technique.

Authors:  Rongkang Gao; Qiang Xue; Yaguang Ren; Hai Zhang; Liang Song; Chengbo Liu
Journal:  Photoacoustics       Date:  2021-12-24

6.  Parallel Computing for Quantitative Blood Flow Imaging in Photoacoustic Microscopy.

Authors:  Zhiqiang Xu; Yiming Wang; Naidi Sun; Zhengying Li; Song Hu; Quan Liu
Journal:  Sensors (Basel)       Date:  2019-09-16       Impact factor: 3.576

7.  Photoacoustic Imaging as a Tool for Assessing Hair Follicular Organization.

Authors:  Ali Hariri; Colman Moore; Yash Mantri; Jesse V Jokerst
Journal:  Sensors (Basel)       Date:  2020-10-16       Impact factor: 3.576

8.  In Vivo Tumor Vascular Imaging with Light Emitting Diode-Based Photoacoustic Imaging System.

Authors:  Marvin Xavierselvan; Mithun Kuniyil Ajith Singh; Srivalleesha Mallidi
Journal:  Sensors (Basel)       Date:  2020-08-12       Impact factor: 3.576

  8 in total

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