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 512×512×159 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 1024×1024×590 voxel images, which is not easy for single processor systems due to the restrictions on the memory space and the processing time.
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Keywords
- Execution Time
- High Performance Computing
- Nonrigid Registration
- Gradient Calculation
- Dynamic Load Balance
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Ino, F., Ooyama, K., Takeuchi, A., Hagihara, K. (2003). Design and Implementation of Parallel Nonrigid Image Registration Using Off-the-Shelf Supercomputers. In: Ellis, R.E., Peters, T.M. (eds) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003. MICCAI 2003. Lecture Notes in Computer Science, vol 2878. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39899-8_41
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DOI: https://doi.org/10.1007/978-3-540-39899-8_41
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