Abstract: A system and method for identifying organisms by analysis of scattergrams of colonies is disclosed. cattergrams are obtained by culturing samples and illuminating the resultant colonies by a laser. The forward scattered light is imaged and subject to a feature extraction process. The feature vector may include Zernike or Chebyshev moments and may also include Harelick texture features. Feature vectors may be used to train a classification process using either supervised or unsupervised machine learning techniques. The classification process may be used to associate a colony phenotype with the genotype of the sample.

Abstract: A system and a method of detecting and characterizing a bacterial colony are presented in which the results are determined within about 48 hours. The bacterial colony is disposed on a substrate and placed between a laser and detector. Light from the laser impinges upon and is scattered by the bacterial colony. The forward scattered light is detected by an optical detector. The signal from the optical detector is analyzed by an analyzer and displayed or supplied to a storage medium for review. As different strains of bacteria possess unique forward scattering fingerprints, the particular strain may be identified.

Abstract: A system and a method of detecting and characterizing a bacterial colony are presented in which the results are determined within about 48 hours. The bacterial colony is disposed on a substrate and placed between a laser and detector. Light from the laser impinges upon and is scattered by the bacterial colony. The forward scattered light is detected by an optical detector. The signal from the optical detector is analyzed by an analyzer and displayed or supplied to a storage medium for review. As different strains of bacteria possess unique forward scattering fingerprints, the particular strain may be identified.