The study of internal structure of materials has always been an essential issue in a variety of application fields, from the medical radiology to the materials science. X-ray computed microtomography (with both conventional and synchrotron radiation sources) has a great potential for these purposes because its three-dimensional and non destructive nature as well as the fact that it does not require any sample preparation and it allows to study samples under stress or after consecutive treatments. The recent developments of new X-ray sources with innovative imaging techniques, as well as novel high resolution detectors, allow moving forward the maximum achievable resolution of this technique to a few micrometers or even less. This contributed to increase its application in biomedical purposes, but also to raise the need for quantitative analysis of the reconstructed data. Indeed in most of the cases a quantitative characterization of the samples microstructures is needed to better understand their physical and chemical behavior, the effects of manufacturing process or the response to stress. Dedicated software packages have been developed to perform a geometrical and morphological characterization of the samples texture and to evaluate some typical parameters commonly used to classify porous media such as porosity, cell size distribution, connectivity and anisotropy. In this work two case studies have been considered for the application of a quantitative analysis approach to microtomography datasets: the first concerns the characterization of bone ingrowth within tissue engineering scaffolds, while the second is related to the extraction of morphological descriptors for the architecture of human skull bones. It will be shown how suitable image processing and analysis techniques are able to effectively quantify significant parameters such as the trabecular thickness of the skull bones as well as the porosity and the degree of connectivity of bone tissue engineering scaffolds. Similar quantitative analysis methods applied to microtomography images have to be considered as an effective methodology for a comprehensive characterization of other biomedical samples.

In this thesis, micro computed tomography (μ−CT) scans of a bio-glass scaffold produced by the robocasting technique was used to create finite element method (FEM) models with the purpose of determining its mechanical strength. Prior to this, a Matlab script was used to create several simplified geometries of the scaffold in an effort to determine the importance of scaffold design parameters (such as the fiber compenetration between two adjacent printing planes) on the strength of the scaffold. Furthermore, to assess the influence of micro-structural defects such as voids and micro-cracks that are intrinsic to the robocasting manufacturing process, the total number of voids and their respective volume was calculated using the μ-CT scan imagery and fitted to a statistical distribution. The distribution of voids was then used to create several scaffold models in Matlab with either spherical or ellipsoidal voids present. In the final two models, one scaled-down and one scaled-up FEM based on μ-CT scans were investigated.To model the crack initiation, propagation and final failure, the phase-field method was used. The method was implemented by the use of a publicly available Fortran user subroutine and was edited to account for asymmetric tension/compression energy degradation. The resulting strength of the produced models have been presented as non-dimensional values. The finite element analysis (FEA) of the Matlab produced scaffolds showed that the fiber shifting between two adjacent layers, porosity, and voids of ellipsoidal shape that were perpendicular to the loading direction had the highest effect on the strength of the scaffold. The resulting normalized strength values obtained from the μ-CT models was partially validated through a comparison with the literature available.The different failure modes and overall architectural arrangement of cracks also showed promising results. / I den här uppsatsen så användes mikrotomografi (μ-CT) skanning av en bio-glas stödstruktur tillverkad av robocasting tekniken för att skapa finita element modeller med syftet att bestämma dess mekaniska styrka. Innan detta så användes ett Matlab-skript för att skapa flera förenklade geometrier av stödstrukturen i ett försök att fastställa betydelsen av viktiga designparametrar (som t.ex fiberpenetrering mellan två intilliggande plan) på stödstrukturens styrka. Vidare, för att bedöma påverkan av mikrostrukturella defekter som tomrum och mikrosprickor som är naturligt förekommande i robocasting-tillverkningsprocessen så uppmättes det totala antal hålrum och deras respektive volym med hjälp av μ-CT-skannade bilder. Denna data blev anpassad till en statistisk fördelning. Fördelningen av tomrum och mikcrosprickor användes sedan för att skapa flera modeller av stödstrukturerna i Matlab med antingen sfäriska eller ellipsoida hålrum närvarande. I de sista två modellerna undersöktes en en nedskalad och en uppskalad finita elementmodell baserad på μ-CT-skanning.För att modellera sprickinitiering, sprickpropagering och slutligen brott användes fasfältsmetoden. Fasfältsmetoden implementerades med hjälp av en för allmänheten tillgänglig Fortran användarrutin som redigerades för att ta hänsyn till en asymmetrisk energidegradering i drag-och tryck. Den resulterande styrkan hos alla modeller har presenterats som icke-dimensionella värden. Finita elementanalysen av Matlab modellerna visade att fiberskiftningen mellan två intilliggande plan, porositet och hålrum med ellipsoid form som var vinkelräta mot belastningsriktningen hade störst effekt på stödstrukturens styrka. De resulterande normaliserade styrkevärdena erhållna från μ-CTmodeller validerades delvis genom en jämförelse med tillgänglig litteratur. Dom olika felmoderna och övergripande strukturella fördelningen av sprickor visade också lovande resultat.