Abstract
Cryo-EM is a method for reconstructing 3D structure of proteins without crystallization. The Expectation-Maximization (EM) algorithm is used in the alignment step of Cryo-EM reconstructions. The EM step is often a serious computational bottleneck for 3D reconstructions. This paper proposes a computationally adaptive version of the EM algorithm that speeds up the algorithm by a factor of 20 − 30. Experiments with noisy real-world data are included to show that the algorithm achieves this speedup without any significant loss of accuracy. Such speed ups are significant, allowing the reconstruction to converge in cpu-days rather than cpu-months.
This research was supported by the grant 5R03LM9328-2 from the National Library of Medicine.
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Tagare, H.D., Sigworth, F., Barthel, A. (2008). Fast, Adaptive Expectation-Maximization Alignment for Cryo-EM. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008. MICCAI 2008. Lecture Notes in Computer Science, vol 5242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85990-1_103
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DOI: https://doi.org/10.1007/978-3-540-85990-1_103
Publisher Name: Springer, Berlin, Heidelberg
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