Automated detection and centring of cryocooled protein crystals

Abstract

A novel method is presented for the automated recognition of cryocooled macromolecular crystals. The method uses several texture-based image-processing algorithms for automated crystal centring, which are able to cope with a variety of crystal morphologies and illumination conditions. The results combined from different algorithms, together with their estimated standard uncertainties, provide a robust determination of the crystal location and allow an internal assessment of their reliability. The method was coded within the software XREC and showed a good performance on 104 sets of images from various beamlines.