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Conf Proc IEEE Eng Med Biol Soc. 2008;2008:1926-9. doi: 10.1109/IEMBS.2008.4649564.

Leveraging genetic algorithm and neural network in automated protein crystal recognition.

Author information

  • 1Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA. ts2060@Columbia.edu


We propose a classification framework combined with a multi-scale image processing method for recognizing protein crystals in high-throughput images. The main three points of the processing method are the multiple population genetic algorithm for region of interest detection, multi-scale Laplacian pyramid filters and histogram analysis techniques to find an effective feature vector. Using human (expert crystallographers) classified images as ground truth, the current experimental results gave 88% true positive and 99% true negative rates, resulting in an average true performance of approximately 93.5% validated on an image database which contained over 79,000 images.

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