@inproceedings{5697c520ee79415fa18e1706f4b4491d,
title = "Covariance estimation using conjugate gradient for 3D classification in CRYO-EM",
abstract = "Classifying structural variability in noisy projections of biological macromolecules is a central problem in Cryo-EM. In this work, we build on a previous method for estimating the covariance matrix of the three-dimensional structure present in the molecules being imaged. Our proposed method allows for incorporation of contrast transfer function and non-uniform distribution of viewing angles, making it more suitable for real-world data. We evaluate its performance on a synthetic dataset and an experimental dataset obtained by imaging a 70S ribosome complex.",
keywords = "3D reconstruction, Cryo-EM, classification, conjugate gradient, covariance, heterogeneity, single particle reconstruction, structural variability",
author = "Joakim Anden and Eugene Katsevich and Amit Singer",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 ; Conference date: 16-04-2015 Through 19-04-2015",
year = "2015",
month = jul,
day = "21",
doi = "10.1109/ISBI.2015.7163849",
language = "English (US)",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
pages = "200--204",
booktitle = "2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015",
address = "United States",
}