Tomographic imaging is both the science and the tool to explore the internal structure of objects. The mission is to use images to characterize the static and/or dynamic properties of the imaged object in order to further integrate these properties into principles, laws or theories. Among the recent trends in tomographic imaging, three-
dimensional (3D) methods are gaining preference and there is the quest for overcoming the bare qualitative observation towards the extraction of quantitative parameters directly from the acquired images.
To this aim, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), as well as the related micro-scale techniques (μ-CT
and μ-MRI), are promising tools for all the fields of science in which non-destructive tests are required. In order to support the interpretation of the images produced by these techniques, there is a growing
demand of reliable image analysis methods for the specific 3D domain. The aim of this thesis is to present approaches for effective
and efficient three-dimensional image analysis with special emphasis on porous media analysis. State-of-the art as well as innovative tools are included in a special software and hardware solution named Pore3D, developed in a collaboration with the Italian 3rd generation synchrotron laboratory Elettra (Basovizza - Trieste, Italy). Algorithms and methods for the characterization of different kinds of porous media are described. The key steps of image segmentation and skeletonization of the segmented pore space are also discussed in depth. Three different clinical and biomedical applications of quantitative
analysis of tomographic images are presented. The reported applications have in common the characterization of the micro-architecture of trabecular bone. The trabecular (or cancellous) bone is a 3D mesh-
work of bony trabeculae and void spaces containing the bone marrow. It can then be thought of as a porous medium with an interconnected porous space. To be more specific, the first application aims
at characterizing a structure (a tissue engineering scaffold) that has
to mimic the architecture of trabecular bone. The relevant features of porosity, pore- and throat-size distributions, connectivity and structural anisotropy indexes are automatically extracted from μ-CT images. The second application is based on ex vivo experiments carried out on femurs and lumbar spines of mice affected by microgravity conditions. Wild type and transgenic mice were hosted in the International Space Station (ISS) for 3 months and the observed bone loss due to the near-zero gravity was quantified by means of synchrotron radiation μ-CT image analysis. Finally, the results of an in vivo study
on the risk of fracture in osteoporotic subjects is reported. The study is based on texture analysis of high resolution clinical magnetic resonance (MR) images.
