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Real-time medical video processing, enabled by hardware accelerated correlations

Thiusius Savarimuthu, Anders Kjaer-Nielsen, Anders Sorensen
The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark
Journal of Real-Time Image Processing (17 December 2010), pp. 1-11

@article{savarimuthureal,

   title={Real-time medical video processing, enabled by hardware accelerated correlations},

   author={Savarimuthu, T.R. and Kj{ae}r-Nielsen, A. and S{o}rensen, A.S.},

   journal={Journal of Real-Time Image Processing},

   pages={1–11},

   issn={1861-8200},

   publisher={Springer}

}

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Image processing involving correlation based filter algorithms have proved extremely useful for image enhancement, feature extraction and recognition, in a wide range of medical applications, but is almost exclusively used with still images due to the amount of computations required by the correlations. In this paper, we present two different practical methods for applying correlation-based algorithms to real-time video images, using hardware accelerated correlation, as well as our results in applying the method to optical venography. The first method employs a GPU accelerated personal computer, while the second method employs an embedded FPGA. We will discuss major difference between the two approaches, and their suitability for clinical use. The system presented detects blood vessels in human forearms in images from NIR camera setup for the use in a clinical environment.
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