Design and implementation of parallel nonrigid image registration using off-the-shelf supercomputers

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Abstract

This paper presents a new parallel algorithm for nonrigid image registration using off-the-shelf supercomputers, or clusters of PCs. Our algorithm realizes scalable registration for high resolution three-dimensional (3-D) images by employing three techniques: (1) data distribution; (2) data-parallel processing; and (3) dynamic load balancing. The experimental results show that our parallel implementation on a cluster of 64 off-the-shelf PCs (with 128 processors) registers liver CT images of 512x512x159 voxels within 8 minutes while a sequential implementation takes 12 hours. Furthermore, our implementation allows processors to use less memory, and thereby enables us to align 1024x1024x590 voxel images, which is not easy for single processor systems due to the restrictions on the memory space and the processing time. © Springer-Verlag Berlin Heidelberg 2003.

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APA

Ino, F., Ooyama, K., Takeuchi, A., & Hagihara, K. (2003). Design and implementation of parallel nonrigid image registration using off-the-shelf supercomputers. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2878, 327–334. https://doi.org/10.1007/978-3-540-39899-8_41

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