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Proceedings Paper

New GPU optimizations for intensity-based registration
Author(s): Razik Yousfi; Guillaume Bousquet; Christophe Chefd'hotel
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Paper Abstract

The task of registering 3D medical images is very computationally expensive. With CPU-based implementations of registration algorithms it is typical to use various approximations, such as subsampling, to maintain reasonable computation times. This may however result in suboptimal alignments. With the constant increase of capabilities and performances of GPUs (Graphics Processing Unit), these highly vectorized processors have become a viable alternative to CPUs for image related computation tasks. This paper describes new strategies to implement on GPU the computation of image similarity metrics for intensity-based registration, using in particular the latest features of NVIDIA's GeForce 8 architecture and the Cg language. Our experimental results show that the computations are many times faster. In this paper, several GPU implementations of two image similarity criteria for both intramodal and multi-modal registration have been compared. In particular, we propose a new efficient and flexible solution based on the geometry shader.

Paper Details

Date Published: 27 March 2009
PDF: 9 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72592O (27 March 2009); doi: 10.1117/12.812455
Show Author Affiliations
Razik Yousfi, Siemens Corporate Research (United States)
Guillaume Bousquet, Siemens Corporate Research (United States)
Christophe Chefd'hotel, Siemens Corporate Research (United States)


Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)

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