Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Computer Vision-Based Image Analysis of Bacteria

Danielsen, Jonas and Nordenfelt, Pontus LU orcid (2017) In Methods in Molecular Biology 1535. p.161-172
Abstract

Microscopy is an essential tool for studying bacteria, but is today mostly used in a qualitative or possibly semi-quantitative manner often involving time-consuming manual analysis. It also makes it difficult to assess the importance of individual bacterial phenotypes, especially when there are only subtle differences in features such as shape, size, or signal intensity, which is typically very difficult for the human eye to discern. With computer vision-based image analysis - where computer algorithms interpret image data - it is possible to achieve an objective and reproducible quantification of images in an automated fashion. Besides being a much more efficient and consistent way to analyze images, this can also reveal important... (More)

Microscopy is an essential tool for studying bacteria, but is today mostly used in a qualitative or possibly semi-quantitative manner often involving time-consuming manual analysis. It also makes it difficult to assess the importance of individual bacterial phenotypes, especially when there are only subtle differences in features such as shape, size, or signal intensity, which is typically very difficult for the human eye to discern. With computer vision-based image analysis - where computer algorithms interpret image data - it is possible to achieve an objective and reproducible quantification of images in an automated fashion. Besides being a much more efficient and consistent way to analyze images, this can also reveal important information that was previously hard to extract with traditional methods. Here, we present basic concepts of automated image processing, segmentation and analysis that can be relatively easy implemented for use with bacterial research.

(Less)
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Bacterial Pathogenesis : Methods and Protocols - Methods and Protocols
series title
Methods in Molecular Biology
editor
Nordenfelt, Pontus and Collin, Matthias
volume
1535
pages
12 pages
publisher
Springer
external identifiers
  • pmid:27914078
  • scopus:85005949211
ISSN
1064-3745
ISBN
978-1-4939-6671-4
978-1-4939-6673-8
DOI
10.1007/978-1-4939-6673-8_10
language
English
LU publication?
yes
id
708ea7d3-506b-4246-be08-4913d1677b62
date added to LUP
2017-02-16 08:01:23
date last changed
2024-02-29 09:07:25
@inbook{708ea7d3-506b-4246-be08-4913d1677b62,
  abstract     = {{<p>Microscopy is an essential tool for studying bacteria, but is today mostly used in a qualitative or possibly semi-quantitative manner often involving time-consuming manual analysis. It also makes it difficult to assess the importance of individual bacterial phenotypes, especially when there are only subtle differences in features such as shape, size, or signal intensity, which is typically very difficult for the human eye to discern. With computer vision-based image analysis - where computer algorithms interpret image data - it is possible to achieve an objective and reproducible quantification of images in an automated fashion. Besides being a much more efficient and consistent way to analyze images, this can also reveal important information that was previously hard to extract with traditional methods. Here, we present basic concepts of automated image processing, segmentation and analysis that can be relatively easy implemented for use with bacterial research.</p>}},
  author       = {{Danielsen, Jonas and Nordenfelt, Pontus}},
  booktitle    = {{Bacterial Pathogenesis : Methods and Protocols}},
  editor       = {{Nordenfelt, Pontus and Collin, Matthias}},
  isbn         = {{978-1-4939-6671-4}},
  issn         = {{1064-3745}},
  language     = {{eng}},
  pages        = {{161--172}},
  publisher    = {{Springer}},
  series       = {{Methods in Molecular Biology}},
  title        = {{Computer Vision-Based Image Analysis of Bacteria}},
  url          = {{http://dx.doi.org/10.1007/978-1-4939-6673-8_10}},
  doi          = {{10.1007/978-1-4939-6673-8_10}},
  volume       = {{1535}},
  year         = {{2017}},
}