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This research shows a new method for estimating the optimal breakpoint in image reconstruction algorithms, suggesting improved accuracy for emission tomography.
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.
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Ruzankin et al. (2026) studied this question.
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