Open Access
25 July 2020 GPU implementation of photoacoustic short-lag spatial coherence imaging for improved image-guided interventions
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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.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Eduardo A. Gonzalez and Muyinatu A. Lediju Bell "GPU implementation of photoacoustic short-lag spatial coherence imaging for improved image-guided interventions," Journal of Biomedical Optics 25(7), 077002 (25 July 2020). https://doi.org/10.1117/1.JBO.25.7.077002
Received: 28 April 2020; Accepted: 29 June 2020; Published: 25 July 2020
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CITATIONS
Cited by 29 scholarly publications.
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KEYWORDS
Visualization

Photoacoustic spectroscopy

Image segmentation

Laser energy

Signal to noise ratio

Coherence imaging

Ultrasonography

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