Development of the Correction Algorithm to Limit the Deformation of Bacterial Colonies Diffraction Patterns Caused by Misalignment and Its Impact on the Bacteria Identification in the Proposed Optical Biosensor.

Igor Buzalewicz,Agnieszka Suchwałko,Alina Wieliczko,Halina Podbielska,Magdalena Karwańska

doi:10.3390/s20205797

Abstract

Recently proposed methods of bacteria identification in optical biosensors based on the phenomenon of light diffraction on macro-colonies offer over 98% classification accuracy. However, such high accuracy relies on the comparable and repeatable spatial intensity distribution of diffraction patterns. Therefore, it is essential to eliminate all non-species/strain-dependent factors affecting the diffraction patterns. In this study, the impact of the bacterial colony and illuminating beam misalignment on the variation of classification features extracted from diffraction patterns was examined. It was demonstrated that misalignment introduced by the scanning module significantly affected diffraction patterns and extracted classification features used for bacteria identification. Therefore, it is a crucial system-dependent factor limiting the identification accuracy. The acceptable misalignment level, when the accuracy and quality of the classification features are not affected, was determined as no greater than 50 µm. Obtained results led to development of image-processing algorithms for determination of the direction of misalignment and concurrent alignment of the bacterial colonies’ diffraction patterns. The proposed algorithms enable the rigorous monitoring and controlling of the measurement’s conditions in order to preserve the high accuracy of bacteria identification.

Highlights

The light diffraction on bacterial colonies has been extensively examined because of the promising potential of this method [1,2,3,4,5,6,7] against alternative destructive techniques based on mass spectroscopy [8,9,10], Raman spectroscopy [11,12,13], or phylogenetics [14,15]
It was demonstrated that the relative misalignment or lateral dislocation of the bacterial colony and the illuminating beam significantly affect intensity distribution of diffraction patterns and, extracted features used in the classification process
The parameter ∆r was introduced as the misalignment of the center of the bacterial colony relative to the center of the fixed illuminating beam cross section, and it can be expressed by the following formula:

Summary

Introduction

The light diffraction on bacterial colonies has been extensively examined because of the promising potential of this method [1,2,3,4,5,6,7] against alternative destructive techniques based on mass spectroscopy [8,9,10], Raman spectroscopy [11,12,13], or phylogenetics [14,15]. The misalignment can be introduced by the sample scanning module and is associated with the minimal achievable movement increment of the used motorized X–Y translational stages and applied scanning and system centering protocols It should be taken into consideration with the other alternative methods based on the forward scattering patterns of bacterial colonies, when the features extraction and classification are based on other approaches, such as the use of Zernike (GPZ) polynomials/moments [6,17,25], which are highly sensitive for any variations of optical signatures symmetry. It was demonstrated that the relative misalignment or lateral dislocation of the bacterial colony and the illuminating beam significantly affect intensity distribution of diffraction patterns and, extracted features used in the classification process It can be treated as a critical system-dependent factor limiting the identification accuracy. The algorithm is a suitable method of automatically monitoring and controlling the measurement’s conditions, enabling the highly accurate bacteria identification based on bacterial colonies’ diffraction patterns

Bacteria

Optical

Classification Features Extracted from Diffraction Patterns

The Dependence of Bacterial Colonies’ Diffraction Patterns on Misalignment

1.66 F-critical

Conclusions