This Article
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrowReprints and Permissions
Right arrow Copyright Information
Right arrow Books from ASM Press
Right arrow MicrobeWorld
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Sieracki, M E
Right arrow Articles by Webb, K L
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Sieracki, M E
Right arrow Articles by Webb, K L
Agricola
Right arrow Articles by Sieracki, M E
Right arrow Articles by Webb, K L

 Previous Article  |  Next Article 

Appl Environ Microbiol. 1989 November; 55(11): 2762-2772

Evaluation of automated threshold selection methods for accurately sizing microscopic fluorescent cells by image analysis.

M E Sieracki, S E Reichenbach and K L Webb

College of William and Mary School of Marine Science, Gloucester Point, Virginia 23062.

ABSTRACT

The accurate measurement of bacterial and protistan cell biomass is necessary for understanding their population and trophic dynamics in nature. Direct measurement of fluorescently stained cells is often the method of choice. The tedium of making such measurements visually on the large numbers of cells required has prompted the use of automatic image analysis for this purpose. Accurate measurements by image analysis require an accurate, reliable method of segmenting the image, that is, distinguishing the brightly fluorescing cells from a dark background. This is commonly done by visually choosing a threshold intensity value which most closely coincides with the outline of the cells as perceived by the operator. Ideally, an automated method based on the cell image characteristics should be used. Since the optical nature of edges in images of light-emitting, microscopic fluorescent objects is different from that of images generated by transmitted or reflected light, it seemed that automatic segmentation of such images may require special considerations. We tested nine automated threshold selection methods using standard fluorescent microspheres ranging in size and fluorescence intensity and fluorochrome-stained samples of cells from cultures of cyanobacteria, flagellates, and ciliates. The methods included several variations based on the maximum intensity gradient of the sphere profile (first derivative), the minimum in the second derivative of the sphere profile, the minimum of the image histogram, and the midpoint intensity. Our results indicated that thresholds determined visually and by first-derivative methods tended to overestimate the threshold, causing an underestimation of microsphere size. The method based on the minimum of the second derivative of the profile yielded the most accurate area estimates for spheres of different sizes and brightnesses and for four of the five cell types tested. A simple model of the optical properties of fluorescing objects and the video acquisition system is described which explains how the second derivative best approximates the position of the edge.


Appl Environ Microbiol. 1989 November; 55(11): 2762-2772




This article has been cited by other articles:

  • Heydorn, A., Nielsen, A. T., Hentzer, M., Sternberg, C., Givskov, M., Ersbøll, B. K., Molin, S. (2000). Quantification of biofilm structures by the novel computer program COMSTAT. Microbiology 146: 2395-2407 [Abstract] [Full Text]  
  • Corvini, P. F. X., Gautier, H., Rondags, E., Vivier, H., Goergen, J. L., Germain, P. (2000). Intracellular pH determination of pristinamycin-producing Streptomyces pristinaespiralis by image analysis. Microbiology 146: 2671-2678 [Abstract] [Full Text]