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• W4288705909 abstract "Abstract This study focused on the problem of projection parameter search in 3D reconstruction using single-particle analysis. We treated the sampling distribution for the parameter search as a prior distribution and designed a probabilistic model for efficient parameter estimation. Using our method, we showed that it is possible to perform 3D reconstruction from synthetic and actual electron microscope images using an initial model and to generate the initial model itself. We also examined whether the optimization function used in the stochastic gradient descent method can be applied with loose constraints to improve the convergence of initial model generation and confirmed the effect. In order to investigate the advantage of generating a smooth sampling distribution from the stochastic model, we compared the distribution of estimated projection directions with the conventional method of performing a global search using spherical gridding. As a result, our method, which is simple in both mathematical model and implementation, showed no algorithmic artifacts." @default.
• W4288705909 created "2022-07-30" @default.
• W4288705909 creator A5035463618 @default.
• W4288705909 creator A5045619381 @default.
• W4288705909 date "2022-07-29" @default.
• W4288705909 modified "2023-09-27" @default.
• W4288705909 title "Estimation of projection parameter distribution and initial model generation in single-particle analysis" @default.
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• W4288705909 doi "https://doi.org/10.1093/jmicro/dfac039" @default.
• W4288705909 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35904535" @default.
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