To cite this abstract / Pentru a cita rezumatul:
Petrisor AI (2004), Geostatistical approaches to microbial image quantification and classification, Doctoral Dissertation, Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA, 149 pp., ISBN 0-496-77726-X
GEOSTATISTICAL APPROACHES TO MICROBIAL IMAGE QUANTIFICATION AND CLASSIFICATION
Alexandru-Ionut Petrisor, PhD Candidate
MSPH, University of South Carolina, Columbia, SC
The study of biofilm properties has been facilitated by advances in microscopy, such as confocal scanning laser microscopy used in conjunction with analytical imaging, digital analysis, and semi-automated image processing. The outcomes of these approaches are enumeration of bacteria, determination of growth, viability, and changing metabolic conditions, assessment of the microstructure of biofilm, micro-environmental analyses, quantification of biodiversity, and computer control of microscope stage. The concept of remote sensing involves the acquisition of information about a system without being in direct contact with it. Therefore, microscopy is a particular type of remote sensing. Traditionally, remote sensing has been used in conjunction with Geographical Information Systems to study small-scale phenomena in geology, geography, and other Earth sciences. The present study is based on the hypothesis that remote sensing and digital image processing techniques can be used in conjunction with Geographical Information Systems and spatial statistics to quantify heterogeneity of the microbiological world at several spatial scales (micrometers to cm). The microbiological system investigated is that of marine stromatolites, the oldest known fossil macrostructures on Earth. Formation of stromatolites continues presently in isolated areas of the Bahamas. The microbially mediated micro-architecture of stromatolites is critical to understanding the global microbial and biogeochemical processes that influence element cycling on Earth, as well as its prehistoric environmental conditions. Of particular interest are microboring processes, calcification and distributions of sulfate-reducers bacteria, analyzed in relationship with the formation of stromatolites. In addition to stromatolites, remote sensing and Geographical Information Systems methods were used to reconstruct and estimate biovolumes, and estimate concentrations of homogeneously sized particles. Polymeric microspheres with known diameters were used to create a ground truth for microscopic structures. Several image enhancement techniques (contrast enhancement and filtering) were compared with regard to their impact on image classification. The results indicated that the approach used in this research represents a viable tool in a field where the development of quantitative imaging is in the early stages. The methodology has a significant potential for automation, and could find more applications in more fundamental microbiological research, and also at different spatial scales of eukaryote cellular biology.