GRAPHICS PROCESSING UNIT ACCELERATED MEDICAL IMAGING Sam Van der Jeught University of Antwerp Belgium New Challenges in the European Area: Young Scientist's.

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Presentation transcript:

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

1 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!

2 Some applications: real-time geometric lens distortion correction Go from input A to output B Wide-angle lens systems suffer from barrel distortion fps

3 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! Regular 2D interpolation on incoming images One-time scattered data interpolation on integer grid of desired size +

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

5 Some applications: real-time geometric lens distortion correction

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

7 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 “Santec inc.”

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

9 Example real-time OCT

10 Real-time GPU-based data processing Considerably faster than CPU Low-cost alternative to data processing boards such as FPGA’s Conclusion

11 Thank you Questions?