A convolutional neural network-based screening tool for X-ray serial crystallography
Journal
Journal of Synchrotron Radiation
Journal Volume
25
Journal Issue
3
Start Page
655
End Page
670
ISSN
1600-5775
Date Issued
2018-04-24
Author(s)
Abstract
A new tool is introduced for screening macromolecular X-ray crystallography diffraction images produced at an X-ray free-electron laser light source. Based on a data-driven deep learning approach, the proposed tool executes a convolutional neural network to detect Bragg spots. Automatic image processing algorithms described can enable the classification of large data sets, acquired under realistic conditions consisting of noisy data with experimental artifacts. Outcomes are compared for different data regimes, including samples from multiple instruments and differing amounts of training data for neural network optimization.
Publisher
International Union of Crystallography (IUCr)
Type
journal article