@inproceedings{be074a1723a5430fa8fab07e8130b077,
title = "An improved correlation method based on rotation invariant feature for automatic particle selection",
abstract = "Particle selection from cryo-electron microscopy (cryo-EM) images is very important for high-resolution reconstruction of macromolecular structure. However, the accuracy of existing selection methods are normally restricted to noise and low contrast of cryo-EM images. In this paper, we presented an improved correlation method based on rotation invariant features for automatic, fast particle selection. We first selected a preliminary particle set applying rotation invariant features, then filtered the preliminary particle set using correlation to reduce the interference of high noise background and improve the precision of correlation method. We used Divide and Conquer technique and cascade strategy to improve the recognition ability of features and reduce processing time. Experimental results on the benchmark of cryo-EM images show that our method can improve the accuracy of particle selection significantly.",
keywords = "Cascade strategy, Correlation, Divide and Conquer, Particle selection, Rotation invariant feature",
author = "Yu Chen and Fei Ren and Xiaohua Wan and Xuan Wang and Fa Zhang",
year = "2014",
doi = "10.1007/978-3-319-08171-7_11",
language = "English",
isbn = "9783319081700",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "114--125",
booktitle = "Bioinformatics Research and Applications - 10th International Symposium, ISBRA 2014, Proceedings",
address = "Germany",
note = "10th International Symposium on Bioinformatics Research and Applications, ISBRA 2014 ; Conference date: 28-06-2014 Through 30-06-2014",
}