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

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Abstract

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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Notes

  1. Warp is a collection of threads assigned to a multiprocessor on the GPU.

  2. Constant memory is fast read only memory for the GPU. The memory can be written from the CPU only.

  3. Global memory is uncached off-chip memory, that is, relatively slow to access.

  4. Texture units are interface used to speed up access to constant memory through caching.

  5. According to the standard formats and rates in the DCAM v1.31 specifications defined by the 1394 Trade Association, the achievable frame rate on a IEEE 1394a (400Mbit) bus is 240 FPS for a 320 × 240 image and 60 FPS for a 640 × 480 image.

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Authors and Affiliations

  1. The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark

    Thiusius Rajeeth Savarimuthu, Anders Kjær-Nielsen & Anders Stengaard Sørensen

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  1. Thiusius Rajeeth Savarimuthu
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  2. Anders Kjær-Nielsen
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  3. Anders Stengaard Sørensen
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Correspondence to Thiusius Rajeeth Savarimuthu.

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Savarimuthu, T.R., Kjær-Nielsen, A. & Sørensen, A.S. Real-time medical video processing, enabled by hardware accelerated correlations. J Real-Time Image Proc 6, 187–197 (2011). https://doi.org/10.1007/s11554-010-0185-2

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  • DOI: https://doi.org/10.1007/s11554-010-0185-2

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