Identification of single bacteria using micro Raman spectroscopy

M. de Biasio; G. McGunnigle; R. Leitner; J. Popp; P. Rösch; D. Balthasar

doi:10.1109/ICSensT.2013.6727612

Identification of single bacteria using micro Raman spectroscopy

M. de Biasio, G. McGunnigle, R. Leitner, J. Popp, P. Rösch, D. Balthasar

Research output: Conference proceeding/Chapter in Book/Report/ › Conference Paper › peer-review

Abstract

We present Raman micro-spectroscopic measurements of Escherichia coli, Bacillus thuringiensis and Staphylococcus cohnii. Several authors have reported successful methods for classifying single bacteria using Raman micro-spectroscopy. The aim of this paper is to evaluate which features of the spectra are useful for the classification. PCA obtained the best performance with 3 PCs. We also tested classifiers based on two and three narrow band filters chosen by exhaustive search. These gave accuracy comparable or greater than that of the PCA based classifier.

Original language	German (Austria)
Title of host publication	2013 Seventh International Conference on Sensing Technology (ICST)
Publisher	IEEE Computer Society
Pages	34-39
Number of pages	6
ISBN (Print)	978-1-4673-5220-8
DOIs	https://doi.org/10.1109/ICSensT.2013.6727612
Publication status	Published - 5 Dec 2013
Externally published	Yes
Event	2013 Seventh International Conference on Sensing Technology (ICST) - Wellington, New Zealand Duration: 3 Dec 2013 → 5 Dec 2013

Conference

Conference	2013 Seventh International Conference on Sensing Technology (ICST)
Period	3/12/13 → 5/12/13

Access to Document

10.1109/ICSensT.2013.6727612

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6727612

Cite this

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title = "Identification of single bacteria using micro Raman spectroscopy",

abstract = "We present Raman micro-spectroscopic measurements of Escherichia coli, Bacillus thuringiensis and Staphylococcus cohnii. Several authors have reported successful methods for classifying single bacteria using Raman micro-spectroscopy. The aim of this paper is to evaluate which features of the spectra are useful for the classification. PCA obtained the best performance with 3 PCs. We also tested classifiers based on two and three narrow band filters chosen by exhaustive search. These gave accuracy comparable or greater than that of the PCA based classifier.",

keywords = "Microorganisms, Principal component analysis, Accuracy, Smoothing methods, Support vector machines, Fingerprint recognition, Band-pass filters",

author = "Biasio, {M. de} and G. McGunnigle and R. Leitner and J. Popp and P. R{\"o}sch and D. Balthasar",

year = "2013",

month = dec,

day = "5",

doi = "10.1109/ICSensT.2013.6727612",

language = "Deutsch ({\"O}sterreich)",

isbn = "978-1-4673-5220-8",

pages = "34--39",

booktitle = "2013 Seventh International Conference on Sensing Technology (ICST)",

publisher = "IEEE Computer Society",

address = "USA/Vereinigte Staaten",

note = "2013 Seventh International Conference on Sensing Technology (ICST) ; Conference date: 03-12-2013 Through 05-12-2013",

}

Biasio, MD, McGunnigle, G, Leitner, R, Popp, J, Rösch, P & Balthasar, D 2013, Identification of single bacteria using micro Raman spectroscopy. in 2013 Seventh International Conference on Sensing Technology (ICST)., 6727612, IEEE Computer Society, pp. 34-39, 2013 Seventh International Conference on Sensing Technology (ICST), 3/12/13. https://doi.org/10.1109/ICSensT.2013.6727612

TY - GEN

T1 - Identification of single bacteria using micro Raman spectroscopy

AU - Biasio, M. de

AU - McGunnigle, G.

AU - Leitner, R.

AU - Popp, J.

AU - Rösch, P.

AU - Balthasar, D.

PY - 2013/12/5

Y1 - 2013/12/5

N2 - We present Raman micro-spectroscopic measurements of Escherichia coli, Bacillus thuringiensis and Staphylococcus cohnii. Several authors have reported successful methods for classifying single bacteria using Raman micro-spectroscopy. The aim of this paper is to evaluate which features of the spectra are useful for the classification. PCA obtained the best performance with 3 PCs. We also tested classifiers based on two and three narrow band filters chosen by exhaustive search. These gave accuracy comparable or greater than that of the PCA based classifier.

AB - We present Raman micro-spectroscopic measurements of Escherichia coli, Bacillus thuringiensis and Staphylococcus cohnii. Several authors have reported successful methods for classifying single bacteria using Raman micro-spectroscopy. The aim of this paper is to evaluate which features of the spectra are useful for the classification. PCA obtained the best performance with 3 PCs. We also tested classifiers based on two and three narrow band filters chosen by exhaustive search. These gave accuracy comparable or greater than that of the PCA based classifier.

KW - Microorganisms

KW - Principal component analysis

KW - Accuracy

KW - Smoothing methods

KW - Support vector machines

KW - Fingerprint recognition

KW - Band-pass filters

UR - https://ieeexplore.ieee.org/document/6727612/

U2 - 10.1109/ICSensT.2013.6727612

DO - 10.1109/ICSensT.2013.6727612

M3 - Konferenzartikel

SN - 978-1-4673-5220-8

SP - 34

EP - 39

BT - 2013 Seventh International Conference on Sensing Technology (ICST)

PB - IEEE Computer Society

T2 - 2013 Seventh International Conference on Sensing Technology (ICST)

Y2 - 3 December 2013 through 5 December 2013

ER -

Identification of single bacteria using micro Raman spectroscopy

Abstract

Conference

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