Speeding up mutual information computation using NVIDIA CUDA hardware

Proceedings - Digital Image Computing Techniques and Applications: 9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007

Volumn , Issue , 2007, Pages 555-560

  Shams, Ramtin ^a   Barnes, Nick ^a  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

DEVICE ARCHITECTURES; DIGITAL IMAGE COMPUTING; EFFICIENT METHODS; GRAPHICS PROCESSOR UNIT (GPU); LIMITED MEMORY; MARGINAL PROBABILITY; MUTUAL INFORMATION (MI); PARALLELIZATION; SYNCHRONIZATION PRIMITIVES;

COMPUTATIONAL METHODS; FEATURE EXTRACTION; GRAPHIC METHODS; IMAGE REGISTRATION; NUMBER THEORY; NUMERICAL METHODS; PATTERN RECOGNITION; STANDARDS; THREE DIMENSIONAL;

CALCULATIONS;

EID: 44949095711     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/DICTA.2007.4426846     Document Type: Conference Paper

References (13)

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10. R. Shams, R. A. Kennedy, P. Sadeghi, and R. Hartley. Gradient intensity-based registration of multi-modal images of the brain. In Proc. IEEE Int. Conf. on Computer Vision (ICCV), Rio de Janeiro, Brazil, Oct. 2007.
11. R. Shams, P. Sadeghi, and R. A. Kennedy. Gradient intensity: A new mutual information based registration method. In Proc. IEEE Computer Vision and Pattern Recognition (CVPR) Workshop on Image Registration and Fusion, Minneapolis, MN, June 2007.
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13. M. Unser and P. Thévenaz. Stochastic sampling for computing the mutual information of two images. In Proceedings of the Fifth International Workshop on Sampling Theory and Applications (SampTA'03), pages 102-109, Strobl, Austria, May 2003.