3D-Printed Models Applied in Medical Research Studies

The aim of this chapter is to show experiments in cardiology and fetal medicine, two specialties of medicine, through the development of three dimensional (3D) physical models produced on additive manufacturing (AM) technologies, also known as 3D printing, from files acquired on noninvasive-imaging technologies (NITs) as 3D ultrasound (3DUS), magnetic resonance imaging (MRI), computed tomography (CT), and micro-computed tomography (micro-CT). The presentation of eight different experiments demonstrates that the combination of AM technologies and files obtained from NITs may improve our understanding of medical anatomical characteristics for medical research, simulation procedures, and educational purposes

Influence of the Cement Film Thickness on the Push-Out Bond Strength of Glass Fiber Posts Cemented in Human Root Canals

The present study evaluated the influence of the cement film thickness on the push-out bond strength of glass fiber posts in the cervical, medium, and apical thirds of root canal spaces. Thirty roots were randomly divided into three groups, according to the fiber post system’s drills: (G1) #2; (G2) #3; (G3) #4. The posts were cemented using a self-adhesive cement, and a small amount of powdered Rhodamine B was used as a stain. Images of both sides of each slice were obtained before and after the push-out test. To determine the cement thickness, a macro routine was developed using the software KS 400. The data were analyzed statistically using Kruskal-Wallis and Dunn’s test. G2 (14.62±5.15 MPa) showed statistically higher bond strength values than G1 (10.04±5.13 MPa) and G3 (7.68±6.14 MPa). All groups presented higher bond strength values in the apical third. The bur diameter significantly influenced the results of the shear bond strength for the push-out test. The slight increase in the cement thickness allowed an increase in the values of shear bond strength when compared to very thin or very thick cement films

An Alternative Approach for Pattern Detection Applied to Materials Characterization

The problem of detecting specific patterns in images of materials obtained through High Resolution Transmission Electron Microscopy is addressed. A supervised classification method is proposed using an extension of Principal Component Analysis and a new a procedure for building the training set. Experiments on two different types of images indicate that the proposed method is superior to the conventional cross-correlation approach. Moreover, using the same number of components, the new dimensionality reduction approach shows a better performance than the standard PCA method

Porosity Characterization of Iron Ore Pellets by X-Ray Microtomography

<div><p>This work proposes a three-dimensional methodology to characterize porosity in iron ore pellets by X-ray Microtomography (microCT). An image analysis routine was developed to discriminate and quantify open/closed porosity. The results were compared to the traditional techniques of mercury intrusion porosimetry (MIP) and optical microscopy (OM). As expected, the porosity values obtained from microCT were much lower than those from MIP and OM, due to the lower spatial resolution of the proposed technique. However, the resolution can be optimized to detect the main peak of the pore size distribution, close to 10 µm. MicroCT was also able to discriminate between open and closed porosities, and revealed the volumetric spatial distribution of the pores, parameters that cannot be obtained from the other techniques. Thus, microCT may become a new standard for this analysis, eliminating the need for specimen preparation (as for OM) or the use of toxic materials (as in MIP).</p></div

Enhancement of oil recovery by emulsion injection: A pore scale analysis from X-ray micro-tomography measurements

International audienceThe efficiency of emulsion injection as an enhanced oil recovery (EOR) method is investigated in a synthetic porous medium consisting of sintered bi-disperse glass beads, which emulates the porosity and permeability of real oil-bearing rocks. Synthetic seawater and an oil-in-water emulsion are successively used to displace a mineral oil which initially saturates the porous space. Micro-CT images with a 4 μm resolution are acquired at the end of the different stages of the process; the water phase is doped with KI to optimize the contrast between the liquid phases. Thus, three-dimensional (3D) images showing the beads, doped water and residual oil present a 3-modal histogram. After denoising with a non-local means filter, alignment and segmentation, the 3D images provide the spatial distributions of the water and oil phases, and thus allow comparing the populations of residual oil ganglia prior to and after the injection of the emulsion. Visual comparison of the spatial phase distributions show that the oil droplets of the oil-water emulsion divert the water path, mobilizing previously trapped oil ganglia. The probability density functions (PDFs) of different geometrical properties of the trapped oil ganglia (104 ganglia with volumes spanning 6 orders of magnitude) after water injection show well defined power law behaviors between a size corresponding to the typical pore throat and that typical of 10 typical pore volumes, and a few very large clusters of sizes between 10 and typical pore volumes. The largest of them alone accounts for 97% of the trapped oil. The same PDFs after emulsion injection demonstrate successful fragmentation of these few very large ganglia, which in this case is the key to efficient EOR procedure through diversion of the water flow by emulsion oil droplets to less permeable regions