Abstract
Fully discretized models for image reconstruction from projections give rise to huge and sparse nonlinear optimization problems. We study the use of parallel and vector supercomputers for the iterative reconstruction of medical images. A block-iterative version of the Multiplicative Algebraic Reconstruction Technique (MART) is implemented on a CRAY X-MP/48. The implementation exploits the block structure of the algorithm which allows us to take advantage both of the vector architecture of the computer and of the multiple processors for parallel computations. Results indicate that block-iterative algorithms are suitable for parallel and vector implementations and can reconstruct with relative efficiency highly discretized images which give rise to very large optimization problems.
| Original language | English |
|---|---|
| Pages (from-to) | 399-415 |
| Number of pages | 17 |
| Journal | Applied Numerical Mathematics |
| Volume | 7 |
| Issue number | 5 |
| DOIs | |
| State | Published - Jun 1991 |
Bibliographical note
Funding Information:The work of S. Zenios was partially supported by NSF grants ECS-8718971 and CCR-8811135 and AFOSR grant 89-0145. The work of Y. Censor was partially supported by NIH grant HL-28438 while the author was with the Medical Image Processing Group (MIPG) at the Department of Radiology of the Hospital of the University of Pennsylvania. We gratefully acknowledge the support of John Gregory from CRAY Research Inc. for providing access to the CRAY X-MP. Helpful discussions with Gabor T. Herman and the programming assistanceo f Samir Gulati are gratefully acknowledged too. A preliminary report of this work was presented at the Fourth Science and Engineering Symposium, October 1988, Mendota Heights, MN [23].
Keywords
- Computerized tomography
- block-iterative algorithms
- entropy maximation
- image reconstruction
- multitasking.
- parallel computing
- vectorization
ASJC Scopus subject areas
- Numerical Analysis
- Computational Mathematics
- Applied Mathematics