Computer Vision-Based Image Analysis of Bacteria

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKapitel samlingsverk

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 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.

Detaljer

Författare
Enheter & grupper
Externa organisationer
  • Lund University
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Medicinsk bildbehandling
  • Radiologi och bildbehandling
Originalspråkengelska
Titel på värdpublikationBacterial Pathogenesis
Undertitel på gästpublikationMethods and Protocols
RedaktörerPontus Nordenfelt, Matthias Collin
FörlagSpringer New York
Sidor161-172
Antal sidor12
Volym1535
ISBN (elektroniskt)978-1-4939-6673-8
ISBN (tryckt)978-1-4939-6671-4
StatusPublished - 2017
PublikationskategoriForskning
Peer review utfördJa

Publikationsserier

NamnMethods in Molecular Biology
Volym1535
ISSN (tryckt)1064-3745