Optofluidic microdevice for algae classification : a comparison of results from discriminant analysis and neural network pattern recognition

A.M. Schaap, Y.J. Bellouard, T. Rohrlack

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

3 Citations (Scopus)
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Abstract

The early detection of changes in the level and composition of algae is essential for tracking water quality and environmental changes. Current approaches require the collection of a specimen which is later analyzed in a laboratory: this slow and expensive approach prevents the rapid identification of changes in algae species dynamics and hinders a quick response to potential outbreaks. In a recent work, we presented a microfluidic chip for classifying and quantifying algae species in water. Here, we study the device performance and specifically compare the difference in results obtained by using a discriminant analysis classification approach and a neural network pattern recognition approach. Using both of these methods, we demonstrate the classification of algae by species, of microspheres by size, and of a detritus/cyanobacteria mixture by type. In each of the demonstrations here, the neural network outperforms the discriminant analysis method.
Original languageEnglish
Title of host publicationProceedings of the Photonics West Conference : Microfluidics, BioMEMS, and Medical Microsystems X, 23 January 2012, San Francisco, California
EditorsH. Becker, B.L. Gray
PublisherSPIE
Pages825104-
DOIs
Publication statusPublished - 2012
Eventconference; Photonics West Conference: Microfluidics, BioMEMS, and Medical Microsystems X -
Duration: 1 Jan 2012 → …

Publication series

NameProceedings of SPIE
Volume8251
ISSN (Print)0277-786X

Conference

Conferenceconference; Photonics West Conference: Microfluidics, BioMEMS, and Medical Microsystems X
Period1/01/12 → …
OtherPhotonics West Conference: Microfluidics, BioMEMS, and Medical Microsystems X

Fingerprint

pattern recognition
discriminant analysis
alga
detritus
cyanobacterium
environmental change
water quality
comparison
water
method

Cite this

Schaap, A. M., Bellouard, Y. J., & Rohrlack, T. (2012). Optofluidic microdevice for algae classification : a comparison of results from discriminant analysis and neural network pattern recognition. In H. Becker, & B. L. Gray (Eds.), Proceedings of the Photonics West Conference : Microfluidics, BioMEMS, and Medical Microsystems X, 23 January 2012, San Francisco, California (pp. 825104-). (Proceedings of SPIE; Vol. 8251). SPIE. https://doi.org/10.1117/12.907012
Schaap, A.M. ; Bellouard, Y.J. ; Rohrlack, T. / Optofluidic microdevice for algae classification : a comparison of results from discriminant analysis and neural network pattern recognition. Proceedings of the Photonics West Conference : Microfluidics, BioMEMS, and Medical Microsystems X, 23 January 2012, San Francisco, California. editor / H. Becker ; B.L. Gray. SPIE, 2012. pp. 825104- (Proceedings of SPIE).
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abstract = "The early detection of changes in the level and composition of algae is essential for tracking water quality and environmental changes. Current approaches require the collection of a specimen which is later analyzed in a laboratory: this slow and expensive approach prevents the rapid identification of changes in algae species dynamics and hinders a quick response to potential outbreaks. In a recent work, we presented a microfluidic chip for classifying and quantifying algae species in water. Here, we study the device performance and specifically compare the difference in results obtained by using a discriminant analysis classification approach and a neural network pattern recognition approach. Using both of these methods, we demonstrate the classification of algae by species, of microspheres by size, and of a detritus/cyanobacteria mixture by type. In each of the demonstrations here, the neural network outperforms the discriminant analysis method.",
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Schaap, AM, Bellouard, YJ & Rohrlack, T 2012, Optofluidic microdevice for algae classification : a comparison of results from discriminant analysis and neural network pattern recognition. in H Becker & BL Gray (eds), Proceedings of the Photonics West Conference : Microfluidics, BioMEMS, and Medical Microsystems X, 23 January 2012, San Francisco, California. Proceedings of SPIE, vol. 8251, SPIE, pp. 825104-, conference; Photonics West Conference: Microfluidics, BioMEMS, and Medical Microsystems X, 1/01/12. https://doi.org/10.1117/12.907012

Optofluidic microdevice for algae classification : a comparison of results from discriminant analysis and neural network pattern recognition. / Schaap, A.M.; Bellouard, Y.J.; Rohrlack, T.

Proceedings of the Photonics West Conference : Microfluidics, BioMEMS, and Medical Microsystems X, 23 January 2012, San Francisco, California. ed. / H. Becker; B.L. Gray. SPIE, 2012. p. 825104- (Proceedings of SPIE; Vol. 8251).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

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AB - The early detection of changes in the level and composition of algae is essential for tracking water quality and environmental changes. Current approaches require the collection of a specimen which is later analyzed in a laboratory: this slow and expensive approach prevents the rapid identification of changes in algae species dynamics and hinders a quick response to potential outbreaks. In a recent work, we presented a microfluidic chip for classifying and quantifying algae species in water. Here, we study the device performance and specifically compare the difference in results obtained by using a discriminant analysis classification approach and a neural network pattern recognition approach. Using both of these methods, we demonstrate the classification of algae by species, of microspheres by size, and of a detritus/cyanobacteria mixture by type. In each of the demonstrations here, the neural network outperforms the discriminant analysis method.

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Schaap AM, Bellouard YJ, Rohrlack T. Optofluidic microdevice for algae classification : a comparison of results from discriminant analysis and neural network pattern recognition. In Becker H, Gray BL, editors, Proceedings of the Photonics West Conference : Microfluidics, BioMEMS, and Medical Microsystems X, 23 January 2012, San Francisco, California. SPIE. 2012. p. 825104-. (Proceedings of SPIE). https://doi.org/10.1117/12.907012