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The GPU on biomedical image processing for color and phenotype analysis

Antonio Ruiz, Manuel Ujaldon, Jose Antonio Andrade
Computer Architecture Dept., University of Malaga, ETSI Informatica. Campus Teatinos, Malaga 29071, Spain
Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, 2007. BIBE 2007.

@conference{ruiz2007gpu,

   title={The GPU on biomedical image processing for color and phenotype analysis},

   author={Ruiz, A. and Ujaldon, M. and Andrades, J.A. and Becerra, J. and Huang, K. and Pan, T. and Saltz, J.},

   booktitle={Bioinformatics and Bioengineering, 2007. BIBE 2007. Proceedings of the 7th IEEE International Conference on},

   pages={1124–1128},

   year={2007},

   organization={IEEE}

}

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The computational power and memory bandwidth of graphics processing units (GPUs) have turned them into attractive platforms for general-purpose applications. In this paper, we exploit this power in the context of biomedical image processing by establishing a cooperative environment between the CPU and the GPU. We deal with phenotype and color analysis on a wide variety of microscopic images from studies of cartilage and bone tissue regeneration using stem cells and genetics involving cancer pathology. Both processors are used in parallel to map algorithms for computing color histograms, contour detection using the Canny filter and pattern recognition based on the Hough transform. Task, data and instruction parallelism are exploited in the GPU to accomplish performance gains between 4times and 100times more than the typical CPU code.
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