Evaluation of crystalline objects in crystallizing protein droplets based on line-segment information in greyscale images.

Several automated crystallization systems have recently been developed for high-throughput X-ray structure analysis. However, the evaluation process for the growth state of crystallizing protein droplets has not yet been completely automated. This paper proposes a new evaluation method for crystalline objects in automated crystallization experiments. The main objective is to determine whether a droplet contains crystals suitable for diffraction experiments and analysis. The evaluation method developed here involves extracting line-segment features from an image of the droplet and discriminating the state of crystallization using classifiers based on line features. In order to verify the efficacy of the proposed method, it was used to classify images obtained by an automated crystallization system.