Detecting Bacteria on Wounds with Hyperspectral Imaging in Fluorescence Mode
Chronic non-healing wounds represent an increasing problem. In order to enable physicians and nurses to make evidence based decisions on wound treatment, the professional societies call for supporting tools to be offered to physicians. Oxygen supply, bacteria colonization and other parameters influe...
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2020-09-01
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Online Access: | https://doi.org/10.1515/cdbme-2020-3067 |
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doaj-6a77e096814c41e7817653139df897d52021-09-06T19:19:29ZengDe GruyterCurrent Directions in Biomedical Engineering2364-55042020-09-016326426710.1515/cdbme-2020-3067cdbme-2020-3067Detecting Bacteria on Wounds with Hyperspectral Imaging in Fluorescence ModeHornberger Christoph.0Herrmann Bert. H.1Daeschlein Georg2Podewils Sebastian von3Sicher Claudia4Kuhn Jana5Masur Kai6Meister Mareike7Wahl Philip8Hochschule Wismar, University of Applied Sciences, Technology, Business and Design, Faculty of Engineering, Philipp-Müller-Str. 14, 23966Wismar, GermanyHochschule Wismar, University of Applied Sciences, Technology, Business and Design, Faculty of Engineering,Wismar, GermanyDepartment of Dermatology of the University Medicine Greifswald,Greifswald, GermanyDepartment of Dermatology of the University Medicine Greifswald,Greifswald, GermanyDepartment of Dermatology of the University Medicine Greifswald,Greifswald, GermanyClinic for Diabetes and Metabolic Diseases, Karlsburg Hospital Dr. Guth GmbH & Co KG, Karlsburg, Germany Leibniz Institute for Plasma Science and Technology,Greifswald, GermanyLeibniz Institute for Plasma Science and Technology,Greifswald, GermanyLeibniz Institute for Plasma Science and Technology,Greifswald, GermanyDiaspective Vision GmbH,Pepelow, GermanyChronic non-healing wounds represent an increasing problem. In order to enable physicians and nurses to make evidence based decisions on wound treatment, the professional societies call for supporting tools to be offered to physicians. Oxygen supply, bacteria colonization and other parameters influence the healing process. So far, these parameters cannot be monitored in an objective and routinely manner. Existing methods like the microbiological analysis of wound swabs, mean a great deal of effort and partly a long delay. In this paper 42 fluorescence images from 42 patients with diabetic foot ulcer, recorded with a hyperspectral imaging system (TIVITA®), converted for fluorescence imaging, were analysed. Beside the fluorescence images, information about the bacterial colonization is available from microbiological analysis of wound swabs. After preprocessing, principal component analysis, PCA, is used for data analysis with a 405 nm excitation wavelength, the emission wavelength range 510 - 745 nm is used for analysis. After dividing the data into a training and a test dataset it could be shown, that bacteria are detectable in the wound area. A quantification in bacterial colonization counts (BCC) was not in the focus of the research in this study stage.https://doi.org/10.1515/cdbme-2020-3067medical smear tests hyperspectral imagingbacteriainfected woundfluorescencediabetic foot ulcerprincipal component analysis pca |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hornberger Christoph. Herrmann Bert. H. Daeschlein Georg Podewils Sebastian von Sicher Claudia Kuhn Jana Masur Kai Meister Mareike Wahl Philip |
spellingShingle |
Hornberger Christoph. Herrmann Bert. H. Daeschlein Georg Podewils Sebastian von Sicher Claudia Kuhn Jana Masur Kai Meister Mareike Wahl Philip Detecting Bacteria on Wounds with Hyperspectral Imaging in Fluorescence Mode Current Directions in Biomedical Engineering medical smear tests hyperspectral imaging bacteria infected wound fluorescence diabetic foot ulcer principal component analysis pca |
author_facet |
Hornberger Christoph. Herrmann Bert. H. Daeschlein Georg Podewils Sebastian von Sicher Claudia Kuhn Jana Masur Kai Meister Mareike Wahl Philip |
author_sort |
Hornberger Christoph. |
title |
Detecting Bacteria on Wounds with Hyperspectral Imaging in Fluorescence Mode |
title_short |
Detecting Bacteria on Wounds with Hyperspectral Imaging in Fluorescence Mode |
title_full |
Detecting Bacteria on Wounds with Hyperspectral Imaging in Fluorescence Mode |
title_fullStr |
Detecting Bacteria on Wounds with Hyperspectral Imaging in Fluorescence Mode |
title_full_unstemmed |
Detecting Bacteria on Wounds with Hyperspectral Imaging in Fluorescence Mode |
title_sort |
detecting bacteria on wounds with hyperspectral imaging in fluorescence mode |
publisher |
De Gruyter |
series |
Current Directions in Biomedical Engineering |
issn |
2364-5504 |
publishDate |
2020-09-01 |
description |
Chronic non-healing wounds represent an increasing problem. In order to enable physicians and nurses to make evidence based decisions on wound treatment, the professional societies call for supporting tools to be offered to physicians. Oxygen supply, bacteria colonization and other parameters influence the healing process. So far, these parameters cannot be monitored in an objective and routinely manner. Existing methods like the microbiological analysis of wound swabs, mean a great deal of effort and partly a long delay. In this paper 42 fluorescence images from 42 patients with diabetic foot ulcer, recorded with a hyperspectral imaging system (TIVITA®), converted for fluorescence imaging, were analysed. Beside the fluorescence images, information about the bacterial colonization is available from microbiological analysis of wound swabs. After preprocessing, principal component analysis, PCA, is used for data analysis with a 405 nm excitation wavelength, the emission wavelength range 510 - 745 nm is used for analysis. After dividing the data into a training and a test dataset it could be shown, that bacteria are detectable in the wound area. A quantification in bacterial colonization counts (BCC) was not in the focus of the research in this study stage. |
topic |
medical smear tests hyperspectral imaging bacteria infected wound fluorescence diabetic foot ulcer principal component analysis pca |
url |
https://doi.org/10.1515/cdbme-2020-3067 |
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