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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
Output data Year: 2026, DOI: 10.1515/jiip-2024-0071
Tags Stopping rule; iterative image reconstruction; emission tomography; OSEM
Authors Ruzankin Pavel S. 1,2 , Denisova Natalya V. 1,2,3
Affiliations
1 Sobolev Institute of Mathematics, Novosibirsk, Russia;
2 Novosibirsk State University , Novosibirsk , Russia
3 Khristianovich Institute of Theoretical and Applied Mechanics , Novosibirsk, Russia ;

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
Dates:
Submitted: Oct 17, 2024
Accepted: Jan 24, 2026
Published online: Feb 21, 2026
Identifiers:
OpenAlex: W7130648402
Citing: Пока нет цитирований
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