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GRAPHICS PROCESSING UNIT ACCELERATED MEDICAL IMAGING

GRAPHICS PROCESSING UNIT ACCELERATED MEDICAL IMAGING. Sam Van der Jeught. New Challenges in the European Area: Young Scientist's 1st International Baku Forum 20-25 th may 2013. University of Antwerp Belgium. Graphics processing units (GPU) as low-cost supercomputers.

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GRAPHICS PROCESSING UNIT ACCELERATED MEDICAL IMAGING

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  1. GRAPHICS PROCESSING UNIT ACCELERATED MEDICAL IMAGING Sam Van der Jeught New Challenges in the European Area: Young Scientist's 1st International Baku Forum 20-25th may 2013 University of Antwerp Belgium

  2. Graphics processing units (GPU) as low-cost supercomputers GT9800, $40USD on ebay Multicore architecture GPU VS single (or double- or quad-) core CPU Parallel programming!

  3. Some applications: real-time geometric lens distortion correction Go from input A to output B Wide-angle lens systems suffer from barrel distortion 1024x1024p @30 fps

  4. Some applications: real-time geometric lens distortion correction Apply general recalibration software to distorted image.Coordinates now have floating point values Scattered data interpolation resamples pixels onto integer grid. Highly time consuming! One-time scattered data interpolation on integer grid of desired size + Regular 2D interpolation on incoming images

  5. Some applications: real-time geometric lens distortion correction After calibration, our algorithm also works on random distortion (not only barrel) (+ video)

  6. Some applications: real-time geometric lens distortion correction

  7. Some applications: optical coherence tomography I Ophthalmology Interferometric imaging technique using infrared light(non-invasive, non- destructive, non-contact) II Detect signature forgeries and hidden layers in paintings

  8. Replace expensive FPGA DAQ board with low-cost GPU Data processing boards can cost up to >$1000 USD Real-time data processing can be achieved with $40 USD GPU Commercial leaflet “Santecinc.”

  9. Example real-time OCT Real-time beating ant heart at 25 fps versus 8 fps on CPU (+video)

  10. Example real-time OCT

  11. Conclusion • Real-time GPU-based data processing • Considerably faster thanCPU • Low-cost alternative to data processing boards such as FPGA’s

  12. Thank youQuestions?

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