Jung, Florian ; Wesarg, Stefan (2010)
3D Registration Based on Normalized Mutual Information : Performance of CPU vs. GPU Implementation.
Bildverarbeitung für die Medizin 2010.
Conference or Workshop Item, Bibliographie
Abstract
Medical image registration is time-consuming but can be sped up employing parallel processing on the GPU. Normalized mutual information (NMI) is a well performing similarity measure for performing multi-modal registration. We present CUDA based solutions for computing NMI on the GPU and compare the results obtained by rigidly registering multi-modal data sets with a CPU based implementation. Our tests with RIRE data sets show a speed-up of factor 5 to 7 for our best GPU implementation.
Item Type: | Conference or Workshop Item |
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Erschienen: | 2010 |
Creators: | Jung, Florian ; Wesarg, Stefan |
Type of entry: | Bibliographie |
Title: | 3D Registration Based on Normalized Mutual Information : Performance of CPU vs. GPU Implementation |
Language: | English |
Date: | 2010 |
Publisher: | Springer, Berlin; Heidelberg; New York |
Series: | Informatik aktuell |
Event Title: | Bildverarbeitung für die Medizin 2010 |
Abstract: | Medical image registration is time-consuming but can be sped up employing parallel processing on the GPU. Normalized mutual information (NMI) is a well performing similarity measure for performing multi-modal registration. We present CUDA based solutions for computing NMI on the GPU and compare the results obtained by rigidly registering multi-modal data sets with a CPU based implementation. Our tests with RIRE data sets show a speed-up of factor 5 to 7 for our best GPU implementation. |
Uncontrolled Keywords: | Forschungsgruppe Medical Computing (MECO), Parallelization, Registration, Medical imaging, Comparison, Compute Unified Device Architecture (CUDA) |
Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Interactive Graphics Systems |
Date Deposited: | 12 Nov 2018 11:16 |
Last Modified: | 12 Nov 2018 11:16 |
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