Title
GPU implementation of photoacoustic short-lag spatial coherence imaging for improved image-guided interventions
Date Issued
01 July 2020
Access level
open access
Resource Type
journal article
Author(s)
Bell M.A.L.
Johns Hopkins University
Publisher(s)
SPIE
Abstract
Significance: Photoacoustic-based visual servoing is a promising technique for surgical tool tip tracking and automated visualization of photoacoustic targets during interventional procedures. However, one outstanding challenge has been the reliability of obtaining segmentations using low-energy light sources that operate within existing laser safety limits. Aim: We developed the first known graphical processing unit (GPU)-based real-time implementation of short-lag spatial coherence (SLSC) beamforming for photoacoustic imaging and applied this real-time algorithm to improve signal segmentation during photoacoustic-based visual servoing with low-energy lasers. Approach: A 1-mm-core-diameter optical fiber was inserted into ex vivo bovine tissue. Photoacoustic-based visual servoing was implemented as the fiber was manually displaced by a translation stage, which provided ground truth measurements of the fiber displacement. GPU-SLSC results were compared with a central processing unit (CPU)-SLSC approach and an amplitude-based delay-and-sum (DAS) beamforming approach. Performance was additionally evaluated with in vivo cardiac data. Results: The GPU-SLSC implementation achieved frame rates up to 41.2 Hz, representing a factor of 348 speedup when compared with offline CPU-SLSC. In addition, GPU-SLSC successfully recovered low-energy signals (i.e., ≤268 μJ) with mean ± standard deviation of signal-to-noise ratios of 11.2 ± 2.4 (compared with 3.5 ± 0.8 with conventional DAS beamforming). When energies were lower than the safety limit for skin (i.e., 394.6 μJ for 900-nm wavelength laser light), the median and interquartile range (IQR) of visual servoing tracking errors obtained with GPU-SLSC were 0.64 and 0.52 mm, respectively (which were lower than the median and IQR obtained with DAS by 1.39 and 8.45 mm, respectively). GPU-SLSC additionally reduced the percentage of failed segmentations when applied to in vivo cardiac data. Conclusions: Results are promising for the use of low-energy, miniaturized lasers to perform GPU-SLSC photoacoustic-based visual servoing in the operating room with laser pulse repetition frequencies as high as 41.2 Hz.
Volume
25
Issue
7
Language
English
OCDE Knowledge area
Oftalmología
Subjects
Scopus EID
2-s2.0-85088624444
PubMed ID
Source
Journal of Biomedical Optics
ISSN of the container
10833668
Sponsor(s)
Funding text
This work was supported by the National Science Foundation CAREER Award ECCS-1751522 and NIH R00-EB018994. The authors acknowledge Dongwoon Hyun for sharing SLSC GPU example code specific to the Verasonics ultrasound imaging system and NVIDIA Corporation for the donation of the Titan Xp GPU used for this research.
Sources of information:
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