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. These efforts have been motivated by the need of realistic microstructures to perform micromechanical studies of grain boundary localized damage phenomenons in steels, one example being the type IV fracture phenomenon occurring in welded joints of grade P91/P92 steel. This failure is attributed to a change of the microstructure due to thermal gradients arising during the welding process. To precisely capture the relationships between microstructural changes and mechanical fields localization in a polycrystalline aggregate, we first need to achieve a reasonable stochastic model of its microstructure, which relies on a detailed knowledge of the microstructural morphology. As martensitic steels possess multiscale microstructures composed of prior austenitic grains, packets and laths, a relevant modelling strategy has to be proposed to account for the observed hierarchies. With this objective, this paper focuses on the larger scale entities present in the microstructure, namely, the austenitic grains.

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. This analysis uses operators from mathematical morphology. The fibril structure is scanned with a directional distance transform. Inertia moments of the directional distances yield the main fibre orientation, corresponding to the main inertia axis. The collaboration of directional distances and fibre orientation delivers a geometrical estimate of the fibre radius. The results include local maps as well as global distribution of orientation and radius of the fibrils over the 3D image. They also bring a segmentation of the image into foreground and background, as well as a classification of the foreground pixels into the preferred orientations. This accurate determination of the spatial arrangement of the fibrils within a 3D data set will be most relevant in biomedical applications. It brings the possibility to monitor remodelling of collagen tissues upon a variety of injuries and to guide tissues engineering because biomimetic 3D organizations and density are requested for better integration of implants.