Single particle imaging with x-ray-free electron lasers enables unique insights into the inner structure of nanometer-sized biological particles such as viruses. In order to reconstruct their 3D composition, a large number of 2D diffraction patterns must be acquired. AI-based isolation of single hits from among the hundreds of thousands of acquisitions made throughout the course of a single experiment is quintessential for the success of the reconstruction.
Assalauova, Dameli, et al. “Classification of diffraction patterns using a convolutional neural network in single-particle-imaging experiments performed at X-ray free-electron lasers.” Journal of Applied Crystallography 55.3 (2022).