@inproceedings{JoubertNBHHS2011,
  title = {Automatic particle picking using diffusion filtering and random forest classification},
  abstract = {An automatic particle picking algorithm for processing
  electron micrographs of a large molecular complex, the
  26S proteasome, is described. The algorithm makes use of a
  coherence enhancing diffusion filter to denoise the data, and a random forest classifier for removing false positives. It does not make use of a 3D reference model, but uses a training set of manually picked particles instead. False positive and false negative rates of around 25% to 30% are achieved on a testing set. The algorithm was developed for a specific particle, but contains steps that should be useful for developing automatic picking algorithms for other particles.},
  pages = {6},
  month = sep,
  year = {2011},
  author = {Joubert, P. and Nickell, S. and Beck, F. and Habeck, M. and Hirsch, M. and Sch{\"o}lkopf, B.},
  month_numeric = {9}
}