Biomedical subjects

M E Sieracki

Publications and source records attributed to M E Sieracki.

4 recordsLinked to original sources

PubMed1992

Measurement of marine picoplankton cell size by using a cooled, charge-coupled device camera with image-analyzed fluorescence microscopy.

Accurate measurement of the biomass and size distribution of picoplankton cells (0.2 to 2.0 microns) is paramount in characterizing their contribution to the oceanic food web and global biogeochemical cycling. Image-analyzed fluorescence microscopy, usually based on video camera technology, allows detailed measurements of individual cells to be taken. The application of an imaging system employing a cooled, slow-scan charge-coupled device (CCD) camera to automated counting and sizing of individual picoplankton cells from natural marine samples is described. A slow-scan CCD-based camera was compared to a video camera and was superior for detecting and sizing very small, dim particles such as fluorochrome-stained bacteria. Several edge detection methods for accurately measuring picoplankton cells were evaluated. Standard fluorescent microspheres and a Sargasso Sea surface water picoplankton population were used in the evaluation. Global thresholding was inappropriate for these samples. Methods used previously in image analysis of nanoplankton cells (2 to 20 microns) also did not work well with the smaller picoplankton cells. A method combining an edge detector and an adaptive edge strength operator worked best for rapidly generating accurate cell sizes. A complete sample analysis of more than 1,000 cells averages about 50 min and yields size, shape, and fluorescence data for each cell. With this system, the entire size range of picoplankton can be counted and measured.

Algorithms↗

PubMed1989

Algorithm to estimate cell biovolume using image analyzed microscopy.

This paper describes an algorithm for calculating the biovolume of cells with simple shapes, such as bacteria, flagellates, and simple ciliates, from a 2-dimensional digital image. The method can be adapted to any image analysis system which allows access to the binary cell image--(i.e., the pixels, or (x,y) points, composing the cell. The cell image is rotated to a standard orientation (horizontal), and a solid of revolution is calculated by digital integration. Verification and a critical assessment of the method are presented. The algorithm accounts for irregularities in cell shape that conventional methods based on length, width, and geometrical formulas do not.

Algorithms↗

PubMed1989

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

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.

Cyanobacteria↗

PubMed1985

Detection, enumeration, and sizing of planktonic bacteria by image-analyzed epifluorescence microscopy.

Epifluorescence microscopy is now being widely used to characterize planktonic procaryote populations. The tedium and subjectivity of visual enumeration and sizing have been largely alleviated by our use of an image analysis system consisting of a modified Artek 810 image analyzer and an Olympus BHT-F epifluorescence microscope. This system digitizes the video image of autofluorescing or fluorochrome-stained cells in a microscope field. The digitized image can then be stored, edited, and analyzed for total count or individual cell size and shape parameters. Results can be printed as raw data, statistical summaries, or histograms. By using a stain concentration of 5 micrograms of 4'6-diamidino-2-phenylindole per ml of sample and the optimal sensitivity level and mode, counts by image analysis of natural bacterial populations from a variety of habitats were found to be statistically equal to standard visual counts. Although the time required to prepare slides, focus, and change fields is the same for visual and image analysis methods, the time and effort required for counting is eliminated since image analysis is instantaneous. The system has been satisfactorily tested at sea. Histograms of cell silhouette areas indicate that rapid and accurate estimates of bacterial biovolume and biomass will be possible with this system.

Bacteriological Techniques↗