Title :
Automated biofilm region recognition and morphology quantification from confocal laser scanning microscopy imaging
Author :
Zielinski, Jerzy S. ; Zielinska, Agnieszka K. ; Bouaynaya, Nidhal ; Vaughan, Justin G. ; Smeltzer, Mark S.
Author_Institution :
Dept. of Appl. Sci., Univ. of Arkansas at Little Rock, Little Rock, AR, USA
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.
Keywords :
image recognition; medical image processing; microorganisms; optical microscopy; COMSTAT software; Staphylococcus aureus; adaptation strategy; antimicrobial treatment; automated biofilm region recognition; confocal laser scanning microscopy imaging; human pathogen; morphology quantification; nosocomial infection; watershed segmentation; Biomass; Biomedical imaging; Image segmentation; Immune system; Rocks; Software; Software algorithms; CLSM; Staphylococcus aureus; biofilm; mathematical morphology; watershed;
Conference_Titel :
Biomedical Sciences and Engineering Conference (BSEC), 2011
Conference_Location :
Knoxville, TN
Print_ISBN :
978-1-61284-411-4
Electronic_ISBN :
978-1-61284-410-7
DOI :
10.1109/BSEC.2011.5872327