In-plane rotation classification for coherent X-ray imaging of single biomolecules

We report a new classification scheme with computation complexity well within the capacity of a PC for coherent X-ray imaging of single biomolecules. In contrast to current methods, which are based on data from large scattering angles, we propose to classify the orientations of the biomolecule using data from small angle scattering, where the signals are relatively strong. Further we integrate data to form radial and azimuthal distributions of the scattering pattern to reduce the variance caused by the shot noise. Classification based on these two distributions are shown to successfully recognize not only the patterns from molecules of the same orientation but also those that differ by an in-plane rotation.