A statistical stopping rule for iterative image reconstruction in emission tomography Full article
| Journal |
Journal of Inverse and Ill-Posed Problems
ISSN: 0928-0219 , E-ISSN: 1569-3945 |
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| Output data | Year: 2026, DOI: 10.1515/jiip-2024-0071 | ||||||
| Tags | Stopping rule; iterative image reconstruction; emission tomography; OSEM | ||||||
| Authors |
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| Affiliations |
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Funding (1)
| 1 |
Министерство науки и высшего образования РФ Mathematical Center in Akademgorodok |
075-15-2019-1613, 075-15-2022-281 |
Abstract:
Image reconstruction in medical emission tomography is an inverse ill-posed problem with Poisson data. Iterative regularization using a statistical stopping rule is studied in this paper. We suggest a new approach to estimate the optimal breakpoint for iterative image reconstruction algorithms in emission tomography. The new method is based on the use of the central limit theorem with a highly accurate normal approximation to the distribution of the suggested statistic under the null hypothesis. In the simulations, our method demonstrated accurate estimates for the optimal breakpoint for iterative algorithms.
Cite:
Ruzankin P.S.
, Denisova N.V.
A statistical stopping rule for iterative image reconstruction in emission tomography
Journal of Inverse and Ill-Posed Problems. 2026. DOI: 10.1515/jiip-2024-0071 OpenAlex
A statistical stopping rule for iterative image reconstruction in emission tomography
Journal of Inverse and Ill-Posed Problems. 2026. DOI: 10.1515/jiip-2024-0071 OpenAlex
Dates:
| Submitted: | Oct 17, 2024 |
| Accepted: | Jan 24, 2026 |
| Published online: | Feb 21, 2026 |
Identifiers:
| OpenAlex: | W7130648402 |
Citing:
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