Bacteria identification in an optical system with optimized diffraction pattern registration condition supported by enhanced statistical analysis.
It is possible to identify bacteria species basing on their diffraction patterns followed by statistical analysis. The new approach exploits two steps: optimization of the recording conditions and introduction of new interpretable features for the identification. First, optimal diffraction registration plane, was determined. Next, results were verified by the analysis workflow based on ANOVA and Fisher divergence for feature selection, QDA and SVM models for classification and identification and CV with stratified sampling, sensitivity and specificity for performance assessment of the identification process. The proposed approach resulted in high sensitivity 0.9759 and specificity 0.9903 with very small identification error 1.34%.
Agnieszka
A
Suchwałko
Igor
I
Buzalewicz
Halina
H
Podbielska
D000465:Algorithms; D001419:Bacteria / Q000737:chemistry*; D004866:Equipment Contamination / Q000706:statistics & numerical data*; D008962:Models, Theoretical; D055096:Optical Devices / Q000382:microbiology*