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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: James C. Wyant
  • Vol. 47, Iss. 5 — Feb. 10, 2008
  • pp: 678–686

High speed classification of individual bacterial cells using a model-based light scatter system and multivariate statistics

Murugesan Venkatapathi, Bartek Rajwa, Kathy Ragheb, Padmapriya P. Banada, Todd Lary, J. Paul Robinson, and E. Daniel Hirleman  »View Author Affiliations


Applied Optics, Vol. 47, Issue 5, pp. 678-686 (2008)
http://dx.doi.org/10.1364/AO.47.000678


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Abstract

We describe a model-based instrument design combined with a statistical classification approach for the development and realization of high speed cell classification systems based on light scatter. In our work, angular light scatter from cells of four bacterial species of interest, Bacillus subtilis,Escherichia coli,Listeria innocua, and Enterococcus faecalis, was modeled using the discrete dipole approximation. We then optimized a scattering detector array design subject to some hardware constraints, configured the instrument, and gathered experimental data from the relevant bacterial cells. Using these models and experiments, it is shown that optimization using a nominal bacteria model (i.e., using a representative size and refractive index) is insufficient for classification of most bacteria in realistic applications. Hence the computational predictions were constituted in the form of scattering-data-vector distributions that accounted for expected variability in the physical properties between individual bacteria within the four species. After the detectors were optimized using the numerical results, they were used to measure scatter from both the known control samples and unknown bacterial cells. A multivariate statistical method based on a support vector machine (SVM) was used to classify the bacteria species based on light scatter signatures. In our final instrument, we realized correct classification of B. subtilis in the presence of E. coli,L. innocua, and E. faecalis using SVM at 99.1 % , 99.6 % , and 98.5 % , respectively, in the optimal detector array configuration. For comparison, the corresponding values for another set of angles were only 69.9 % , 71.7 % , and 70.2 % using SVM, and more importantly, this improved performance is consistent with classification predictions.

© 2008 Optical Society of America

OCIS Codes
(120.5820) Instrumentation, measurement, and metrology : Scattering measurements
(170.1530) Medical optics and biotechnology : Cell analysis
(290.5850) Scattering : Scattering, particles

ToC Category:
Instrumentation, Measurement, and Metrology

History
Original Manuscript: May 14, 2007
Revised Manuscript: November 29, 2007
Manuscript Accepted: November 30, 2007
Published: February 7, 2008

Virtual Issues
Vol. 3, Iss. 3 Virtual Journal for Biomedical Optics

Citation
Murugesan Venkatapathi, Bartek Rajwa, Kathy Ragheb, Padmapriya P. Banada, Todd Lary, J. Paul Robinson, and E. Daniel Hirleman, "High speed classification of individual bacterial cells using a model-based light scatter system and multivariate statistics," Appl. Opt. 47, 678-686 (2008)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-47-5-678

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