Automated biofilm region recognition and morphology quantification from confocal laser scanning microscopy imaging

Jerzy S. Zielinski, Agnieszka K. Zielinska, Nidhal Bouaynaya, Justin G. Vaughan, Mark S. Smeltzer

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

2 Scopus citations

Abstract

Staphylococcus aureus is an opportunistic human pathogen and a primary cause of nosocomial infections. Its biofilm forming capability is an adaptation strategy utilized by many species of bacteria to overcome stressful environmental conditions and provides both resistance to antimicrobial treatments and protection from the host immune system. This paper addresses a growing demand for an objective, fully automated method of biofilm structure description with standardized parameters that are independent of user input. In this study, we used watershed segmentation to analyze and compare confocal laser scanning microscopy (CLSM) images of two S. aureus strains with different biofilm-forming capabilities. Results are compared with manual calculations as well as the commonly used COMSTAT software.

Original languageEnglish (US)
Title of host publicationProceedings of the 2011 Biomedical Sciences and Engineering Conference
Subtitle of host publicationImage Informatics and Analytics in Biomedicine, BSEC 2011
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 Biomedical Sciences and Engineering Conference: Image Informatics and Analytics in Biomedicine, BSEC 2011 - Knoxville, TN, United States
Duration: Mar 15 2011Mar 17 2011

Publication series

NameProceedings of the 2011 Biomedical Sciences and Engineering Conference: Image Informatics and Analytics in Biomedicine, BSEC 2011

Other

Other2011 Biomedical Sciences and Engineering Conference: Image Informatics and Analytics in Biomedicine, BSEC 2011
Country/TerritoryUnited States
CityKnoxville, TN
Period3/15/113/17/11

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Biomedical Engineering

Fingerprint

Dive into the research topics of 'Automated biofilm region recognition and morphology quantification from confocal laser scanning microscopy imaging'. Together they form a unique fingerprint.

Cite this