The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Algebraic reconstruction techniques can be made computationally efficient (positron emission tomography application)
Abstract
Algebraic reconstruction techniques (ART) are iterative procedures for recovering objects from their projections. It is claimed that by a careful adjustment of the order in which the collected data are accessed during the reconstruction procedure and of the so-called relaxation parameters that are to be chosen in an algebraic reconstruction technique, ART can produce high-quality reconstructions with excellent computational efficiency. This is demonstrated by an example based on a particular (but realistic) medical imaging task, showing that ART can match the performance of the standard expectation-maximization approach for maximizing likelihood (from the point of view of that particular medical task), but at an order of magnitude less computational cost.
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Citations
Cites
Maximum Likelihood Reconstruction for Emission Tomography
Shepp, L. A., & Vardi, Y. (1982) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.1982.4307558 · Cited by 4,429
Gordon, R., Bender, R., & Herman, G. T. (1970) · Journal of Theoretical Biology · doi:10.1016/0022-5193(70)90109-8 · Cited by 2,791
Self-citationImage reconstruction from projections : the fundamentals of computerized tomography
Herman, G. T. (1980) · Academic Press eBooks · Cited by 1,993
Self-citationImplementing and Accelerating the EM Algorithm for Positron Emission Tomography
Kaufman, L. (1987) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.1987.4307796 · Cited by 293
Positron emission tomography imaging of regional cerebral glucose metabolism
Alavi, A. A., Dann, R., Chawluk, J. B., Alavi, J. Β., Kushner, M., & Reivich, M. (1986) · Seminars in Nuclear Medicine · doi:10.1016/s0001-2998(86)80002-2 · Cited by 134
Introduction to Medical Statistics.
Murray, G. D., & Bland, M. (1990) · Biometrics · doi:10.2307/2531667 · Cited by 127
Herman, G. T., & Odhner, D. (1991) · IEEE Transactions on Medical Imaging · doi:10.1109/42.97583 · Cited by 104
Self-citationIterative Methods for Image Reconstruction
Fessler, J. A. (2006) · Cited by 42
Cited by
Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm
Needell, D., Srebro, N., & Ward, R. (2016) · Mathematical Programming · doi:10.1007/s10107-015-0864-7 · Cited by 432
Metadata
- Authors
- Herman, G. T., & Meyer, L. B.
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 1993
- Volume
- 12
- Issue
- 3
- Pages
- 600-609
- ISSN
- 0278-0062 (ISSN-L)
- OpenAlex
- W2135294617
- Cited by
- 486
- References
- 8
- FWCI
- 6.05
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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