Morphological modelling of three-phase microstructures of anode layers using SEM images.

A general method is proposed to model 3D microstructures representative of three-phases anode layers used in fuel cells. The models are based on SEM images of cells with varying morphologies. The materials are first characterized using three morphological measurements: (cross-)covariances, granulometry and linear erosion.

Modeling of the Multiscale Dispersion of Nanoparticles in a Hematite Coating.

Images of a hematite-based epoxy coating are obtained by scanning electron microscopy (SEM). At the scale of a few micrometers, they show aggregates of hematite nano-particles organized along thin curved channels. We first segment the images and analyze them using mathematical morphology.

Modelling mesoporous alumina microstructure with 3D random models of platelets.

This work focuses on a mesoporous material made up of nanometric alumina 'platelets' of unknown shape. We develope a 3D random microstructure to model the porous material, based on 2D transmission electron microscopy (TEM) images, without prior knowledge on the spatial distribution of alumina inside the material. The TEM images, acquired on samples with thickness 300 nm, a scale much larger than the platelets's size, are too blurry and noisy to allow one to distinguish platelets or platelets aggregates individually.

Stereological reconstruction of polycrystalline materials.

Laguerre tessellations are suitable models for many polycrystalline materials. In this work, we present a reconstruction-based approach to fit a spatial Laguerre tessellation model to a plane section of a cellular material under the condition that one section of the model resembles the observed section of the material. To account for this special requirement, we introduce a novel Euclidean distance-based criterion for the model fitting.

Direct estimation of austenitic grain dimensions in heat affected zones of a martensitic steel from EBSD images.

In the context of automated analyses of electron-backscattered-diffraction images, we present in this paper a novel method to automatically extract morphological properties of prior austenitic grains in martensitic steels based on raw crystallographic orientation maps. This quantification includes the estimation of the mean chord length in specific directions, with in addition the reconstruction of the mean shape of austenitic grains inducing anisotropic shape properties. The approach is based on the morphological measure of covariance on a decision curve of grain fidelity per disorientation angle.

Three-dimensional morphological modelling of concrete using multiscale Poisson polyhedra.

This paper aims at developing a random morphological model for concrete microstructures. A 3D image of concrete is obtained by microtomography and is used in conjunction with the concrete formulation to build and validate the model through morphological measurements. The morphological model is made up of two phases, corresponding to the matrix, or cement paste and to the aggregates.

Quantitative comparison of segmentation algorithms for FIB-SEM images of porous media.

Focused ion beam tomography has proven to be capable of imaging porous structures on a nano-scale. However, due to shine-through artefacts, common segmentation algorithms often lead to severe dislocation of individual structures in z-direction. Recently, a number of approaches have been developed, which take into account the specific nature of focused ion beam-scanning electron microscope images for porous media.

Imaging tools for analysis of the ureteric tree in the developing mouse kidney.

The structure of the ureteric tree in developing mouse and rat kidneys has previously been quantified in two dimensions. While this type of analysis may provide evidence of changes in ureteric growth, these measurements are effectively inaccurate, as the ureteric tree is a three-dimensional (3D) object. Here we describe a method for measuring the ureteric tree in three dimensions.

Morphological segmentation of FIB-SEM data of highly porous media.

Nanoporous materials play an important role in modern batteries as well as fuel cells. The materials microstructure needs to be analyzed as it determines the electrochemical properties. However, the microstructure is too fine to be resolved by microcomputed tomography.

3D multiscale segmentation and morphological analysis of X-ray microtomography from cold-sprayed coatings.

X-ray microtomography from cold-sprayed coatings brings a new insight on this deposition process. A noise-tolerant segmentation algorithm is introduced, based on the combination of two segmentations: a deterministic multiscale segmentation and a stochastic segmentation. The stochastic approach uses random Poisson lines as markers.

Imaging and 3D morphological analysis of collagen fibrils.

The recent booming of multiphoton imaging of collagen fibrils by means of second harmonic generation microscopy generates the need for the development and automation of quantitative methods for image analysis. Standard approaches sequentially analyse two-dimensional (2D) slices to gain knowledge on the spatial arrangement and dimension of the fibrils, whereas the reconstructed three-dimensional (3D) image yields better information about these characteristics. In this work, a 3D analysis method is proposed for second harmonic generation images of collagen fibrils, based on a recently developed 3D fibre quantification method.

TEM image analysis and modelling: application to boehmite nanoparticles.

Boehmite occurs in the form of nanoparticles. Upon drying, it can form the alumina that is common in catalyst support used in refining and petrochemicals. The topotactic transformation of boehmite alumina led to an interest in the precise shape and size of these nanoparticles which is highly linked to the catalyst activity.

Random-walk-based stochastic modeling of three-dimensional fiber systems.

For the simulation of fiber systems, there exist several stochastic models: systems of straight nonoverlapping fibers, systems of overlapping bending fibers, or fiber systems created by sedimentation. However, there is a lack of models providing dense, nonoverlapping fiber systems with a given random orientation distribution and a controllable level of bending. We introduce a new stochastic model in this paper that generalizes the force-biased packing approach to fibers represented as chains of balls.

A multiscale microstructure model of carbon black distribution in rubber.

The increase of observations and computational capabilities favoured the numerical simulation of microstructure to derive the effective properties of materials. Indeed, the multiscale approaches, that use homogenization techniques, enable us to estimate or to give bounds of the overall properties of heterogeneous media. In this work, the objective is to develop a three-dimensional mathematical model of the morphology of the microstructure of rubber composite containing carbon black nano-fillers.

Texture classification by statistical learning from morphological image processing: application to metallic surfaces.

A classification method based on textural information for metallic surfaces displaying complex random patterns is proposed. Because these kinds of textures show fluctuations at a small scale and some uniformity at a larger scale, a probabilistic approach is followed, considering textural variations as realizations of random functions. Taking into account information of pixel neighbourhoods, the texture for each pixel is described at different scales.

Segmentation of 3D microtomographic images of granular materials with the stochastic watershed.

Segmentation of 3D images of granular materials obtained by microtomography is not an easy task. Because of the conditions of acquisition and the nature of the media, the available images are not exploitable without a reliable method of extraction of the grains. The high connectivity in the medium, the disparity of the object's shape and the presence of image imperfections make classical segmentation methods (using image gradient and watershed constrained by markers) extremely difficult to perform efficiently.

A quantitative morphological analysis of nanostructured ceria-silica composite catalysts.

This study aims at examining the morphology of different catalysts, which are based on a dispersion of ceria nanoparticles embedded in a high surface area mesoporous silica framework. In order to fully describe the mesostructured composite material, we propose here a quantitative description of the microstructure based on a quantitative analysis of micrographs that were obtained via high-resolution transmission electron microscopy. We have therefore developed an automatic image analysis process in order to automatically and efficiently extract all the components of the catalyst images.

Reconstruction of the rose of directions from a digital microhologram of fibres.

Digital holography makes it possible to acquire quickly the interference patterns of objects spread in a volume. The digital processing of the fringes is still too slow to achieve on line analysis of the holograms. We describe a new approach to obtain information on the direction of illuminated objects.

Direct extraction of the mean particle size from a digital hologram.

Digital holography, which consists of both acquiring the hologram image in a digital camera and numerically reconstructing the information, offers new and faster ways to make the most of a hologram. We describe a new method to determine the rough size of particles in an in-line hologram. This method relies on a property that is specific to interference patterns in Fresnel holograms: Self-correlation of a hologram provides access to size information.

Computer-based detection of neonatal changes to branching morphogenesis reveals different mechanisms of and predicts prostate enlargement in mice haplo-insufficient for bone morphogenetic protein 4.

Early changes to branching morphogenesis of the prostate are believed to lead to enlargement of the gland in adult life. However, it has not been possible to demonstrate directly that alterations to branching during the developmental period have a permanent effect on adult prostate size. In order to examine branching morphogenesis in a quantitative manner in neonatal mice, a combination of imaging and computational technology was used to detect and quantify branching using bone morphogenetic protein 4 haplo-insufficient mice that develop enlarged prostate glands in adulthood.

Exogenous BMP-4 amplifies asymmetric ureteric branching in the developing mouse kidney in vitro.

Background: Exogenous bone morphogenetic protein 4 (BMP-4) has been reported to inhibit ureteric branching morphogenesis and regulate the anterior-posterior axis of the developing kidney in vitro. We examined the role of BMP-4 on ureteric branching in vitro using three-dimensional image analysis software and statistical models. Additionally, in vivo ureteric branching was analyzed and the effect of reduced levels of BMP-4 in vivo on nephron number was examined.

Quantitation of 3D ureteric branching morphogenesis in cultured embryonic mouse kidney.

The growth and branching of the epithelial ureteric tree is critical for development of the permanent kidney (metanephros). Current methods of analysis of ureteric branching are mostly qualitative. We have developed a method for measuring the length of individual branches, and thereby the total length of the ureteric tree in 3 dimensions (3D).

On the orientational analysis of planar fibre systems from digital images.

The orientational characteristics of fibres in digital images are studied. The fibres are modelled by a planar Boolean model whose typical grain is a thick (coloured) fibre. The aim is to make stereological inference on the rose of directions of the unobservable central fibres from observations made on a digital image of the thick fibres.