H. Vivier

Particle morphology: from visualisation to measurement

The main steps of characterisation of particle morphology by image analysis, i.e., visualisation, image treatment, shape quantification, for routine use in powder technology are reviewed and illustrated by examples. Macroscale and mesoscale bidimensional descriptors are presented, depending upon the desired level of detail. Elements for a quantification of the 3D shape are given, stressing out the special case of faceted particles. The difficulties of comparing the size measurements by image analysis with those obtained by other methods (laser diffraction granulometers, sieving) are discussed.

Characterisation of activated sludge by automated image analysis

An automated image analysis procedure has been developed for the simultaneous characterisation of flocs (projected diameter and fractal dimension) and filamentous bacteria (filament length) of fresh activated sludge samples observed by optical microscopy. It has been used to monitor, over a period of 1 year, the activated sludge of a large municipal wastewater treatment plant, located in an area subject to mild continental weather. No relationship could be established between floc characteristics and the sludge volume index (SVI). Filamentous bulking events associated with variations of the SVI were detected from changes of total filament length, of filament number/image and of the proportion of filamentous bacteria with respect to the total activated sludge. The proposed automated method provides quantitative support for the classification of bulking events.

Effect of precipitation conditions on the morphology of calcium carbonate : quantification of crystal shapes using image analysis

Extra-pure calcium carbonate was obtained in the laboratory by carbonation of a solution of calcium nitrate and monoethanolamine with carbon(IV) oxide under various operating conditions. The particle size and shape of the samples obtained were characterized by image analysis. The results show that the method of quantitative morphological characterization using defined shape descriptors enables us to get a better insight into the relationship of the mineralogical composition and particle size/shape to precipitation conditions.

Morphological analysis of pharmaceutical powders

Within the framework of routine application of image analysis in a pharmaceutical laboratory, a compromise should be established between the number of particles, the analysis time and the accuracy of the results. In the case of nonacicular particles, 500 particles constitute the minimal set to be analysed to get basic information on size and shape distributions. The best choice is 1000 to 1500 particles. As complex shapes should be described by a set of parameters, statistical data mining techniques allow to globally compare samples from the point of view of their size and morphology. For acicular particles, frequently seen in pharmaceutical powders, an algorithm based on the Hough transform and the Euclidian Distance Map transform has been developed: it allows to estimate the length and the breadth of the particles, even when they are in (limited) contact with one another.

Biomass Quantification by Image Analysis

Microbiologists have always rely on microscopy to examine microorganisms. When microscopy, either optical or electron-based, is coupled to quantitative image analysis, the spectrum of potential applications is widened: counting, sizing, shape characterization, physiology assessment, analysis of visual texture, motility studies are now easily available for obtaining information on biomass. In this chapter the main tools used for cell visualization as well as the basic steps of image treatment are presented. General shape descriptors can be used to characterize the cell morphology, but special descriptors have been defined for filamentous microorganisms. Physiology assessment is often based on the use of fluorescent dyes. The quantitative analysis of visual texture is still limited in bioengineering but the characterization of the surface of microbial colonies may open new prospects, especially for cultures on solid substrates. In many occasions, the number of parameters extracted from images is so large that data-mining tools, such as Principal Components Analysis, are useful for summarizing the key pieces of information.

Semi-automated recognition of protozoa by image analysis

A programme was created to semi-automatically analyse protozoal digitised images. Principal Component Analysis technique was used for species identification. After data collection and mathematical treatment, a three-dimensional representation was generated and several protozoa (Opercularia, Colpidium, Tetrahymena, Prorodon, Glaucoma and Trachelophyllum) species could be positively identified.

Physiological investigations by image analysis.

Modern quantitative image analysis has been extensively used to characterize the morphology of microorganisms, especially those of the filamentous type. More recently physiological features have been quantified, making use of classical stains as well as fluorescent dyes. The potential of the technique is illustrated by a detailed analysis of the differentiation of Streptomyces ambofaciens. Three different staining procedures have been used to monitor the thinning and septation of hyphae (with propidium iodide staining), the leakage of cellular components through the membrane (with carbol gentian violet staining) and the respiration (with INT staining) in a batch submerged culture.

Morphological characterisation of gibbsite and alumina

By combining visualisation by scanning electron microscopy (SEM), optical microscopy (OM) with aniline as an immersion liquid and semiautomated image analysis procedures, the external and internal structures of different types of gibbsite and alumina particles have been characterised. These techniques are complementary to other methods such as BET for alumina or mercury porosimetry for gibbsite: relations were established between the individual morphological and structural characteristics of the tested powders (shape, degree of mosaicity, structure homogeneity) and the global information provided by BET and mercury porosimetry.

Quantitative characterization of cellular differentiation of Streptomyces ambofaciens in submerged culture by image analysis

Image analysis methods were developed for light and epifluorescence microscopy of Streptomyces ambofaciens undergoing differentiation in submerged culture. Grey level images were obtained with an integration controlled CCD camera and allowed three parameters to be measured: occurence of empty zones in mycelium, number of septations, mycelium thickness.

The study of protozoa population in wastewater treatment plants by image analysis

Protozoa are important microorganisms for the ecosystem balance in wastewater treatment plants. A procedure for their semi-automated identification and counting based on image analysis is proposed. The main difficulty is segmentation of the protozoa as most of them are in contact with the sludge. The protozoa are characterized by the size of their silhouette (area and length) and three shape factors (elongation, circularity and eccentricity). They are identified after projecting the resulting 5D space into a 3D space of principal components. The rate of automated identification is actually higher than 50% for some of the species commonly found in activated sludge.