2014
DOI: 10.1117/1.jbo.19.7.071410
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Parallelized multi–graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy

Abstract: Abstract. Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multigraphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPU… Show more

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Cited by 23 publications
(9 citation statements)
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“…We recently leveraged the capability of graphic processing units (Two NVIDIA GTX Titan cards) to allow real time acquisition and visualization of high resolution images. 34 …”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…We recently leveraged the capability of graphic processing units (Two NVIDIA GTX Titan cards) to allow real time acquisition and visualization of high resolution images. 34 …”
Section: Methodsmentioning
confidence: 99%
“…The acquisition time of the 3D image was 30 seconds and the visualization of the sample was made possible within 13 seconds of the acquisition time using the parallelized GPU processing. 34 For each measurement, 1000 frames, each containing 1000 pixels (A-scans), were saved for further image analysis.…”
Section: Methodsmentioning
confidence: 99%
“…As example of a GDOCM image of a human fingertip acquired with three zones and the corresponding fusing procedure is shown in Figure 4. Parallel processing of the acquired data on graphics processing units (GPUs) achieves near real-time visualization of the volumetric images [28].…”
Section: Gabor-domain Optical Coherence Microscopymentioning
confidence: 99%
“…Although we leveraged the parallel computing toolbox, the CPU computing is fundamentally limited by the number of cores available. In future work, we plan to leverage the GPU framework we recently implemented in our lab to significantly speed up the post processing time and allow for real time visualization of thickness maps [23]. Fig.…”
Section: Processing Speedmentioning
confidence: 99%