Virtual Reality applied to biomedical engineering

Actualment, la realitat virtual esta sent tendència i s'està expandint a l'àmbit mèdic, fent possible l'aparició de nombroses aplicacions dissenyades per entrenar metges i tractar pacients de forma més eficient, així com optimitzar els processos de planificació quirúrgica. La necessitat mèdica i objectiu d'aquest projecte és fer òptim el procés de planificació quirúrgica per a cardiopaties congènites, que compren la reconstrucció en 3D del cor del pacient i la seva integració en una aplicació de realitat virtual. Seguint aquesta línia s’ha combinat un procés de modelat 3D d’imatges de cors obtinguts gracies al Hospital Sant Joan de Déu i el disseny de l’aplicació mitjançant el software Unity 3D gracies a l’empresa VISYON. S'han aconseguit millores en quant al software emprat per a la segmentació i reconstrucció, i s’han assolit funcionalitats bàsiques a l’aplicació com importar, moure, rotar i fer captures de pantalla en 3D de l'òrgan cardíac i així, entendre millor la cardiopatia que s’ha de tractar. El resultat ha estat la creació d'un procés òptim, en el que la reconstrucció en 3D ha aconseguit ser ràpida i precisa, el mètode d’importació a l’app dissenyada molt senzill, i una aplicació que permet una interacció atractiva i intuïtiva, gracies a una experiència immersiva i realista per ajustar-se als requeriments d'eficiència i precisió exigits en el camp mèdic

In-Situ Defect Detection in Laser Powder Bed Fusion by Using Thermography and Optical Tomography—Comparison to Computed Tomography

Among additive manufacturing (AM) technologies, the laser powder bed fusion (L-PBF) is one of the most important technologies to produce metallic components. The layer-wise build-up of components and the complex process conditions increase the probability of the occurrence of defects. However, due to the iterative nature of its manufacturing process and in contrast to conventional manufacturing technologies such as casting, L-PBF offers unique opportunities for in-situ monitoring. In this study, two cameras were successfully tested simultaneously as a machine manufacturer independent process monitoring setup: a high-frequency infrared camera and a camera for long time exposure, working in the visible and infrared spectrum and equipped with a near infrared filter. An AISI 316L stainless steel specimen with integrated artificial defects has been monitored during the build. The acquired camera data was compared to data obtained by computed tomography. A promising and easy to use examination method for data analysis was developed and correlations between measured signals and defects were identified. Moreover, sources of possible data misinterpretation were specified. Lastly, attempts for automatic data analysis by data integration are presented

First results from SAM-FP: Fabry-Perot observations with ground-layer adaptive optics - the structure and kinematics of the core of 30 Doradus

The aim of this paper is to present the first data set obtained with SOAR Adaptive Module-Fabry-Parot (SAM-FP), a Fabry-Perot instrument mounted inside the SOAR telescope Adaptive-Optics Module. This is the only existing imaging Fabry-Perot interferometer using laser-assisted ground-layer adaptive optics. SAM-FP was used to observe the ionized gas, traced by Halpha, in the centre of the 30 Doradus starburst (the Tarantula Nebula) in the Large Magellanic Cloud, with high spatial (~0.6" or 0.15 pc) and spectral (R=11200) resolution. Radial velocity, velocity dispersion and monochromatic maps were derived. The region displays a mix of narrow, sigma ~ 20 km/s profiles and multiple broader profiles with sigma ~ 70-80 km/s, indicating the complex nature of the nebula kinematics. A comparison with previously obtained VLT/FLAMES spectroscopy demonstrates that the data agree well in the regions of overlap, but the Fabry-Perot data are superior in spatial coverage. A preliminary analysis of the observations finds a new expanding bubble south of R136, with a projected radius of r=5.6 pc and an expansion velocity of 29 +/- 4 km/s. In addition, the first-time detailed kinematic maps derived here for several complexes and filaments of 30 Doradus allow identification of kinematically independent structures. These data exemplify the power of the combination of a high-order Fabry-Perot with a wide-field imager (3' x 3' GLAO-corrected field of view) for high-resolution spatial and spectral studies. In particular, SAM-FP data cubes are highly advantageous over multifibre or long-slit data sets for nebula structure studies and to search for small-scale bubbles, given their greatly improved spatial coverage. For reference, this paper also presents two appendices with detailed descriptions of the usage of Fabry-Perot devices, including formulae and explanations for understanding Fabry-Perot observations.Comment: 22 pages, 9 figures, 1 tabl

Automated Design of Tissue Engineering Scaffolds by Advanced CAD

The design of scaffolds with an intricate and controlled internal structure represents a challenge for Tissue Engineering. Several scaffold manufacturing techniques allow the creation of complex and random architectures, but have little or no control over geometrical parameters such as pore size, shape and interconnectivity- things that are essential for tissue regeneration. The combined use of CAD software and layer manufacturing techniques allow a high degree of control over those parameters, resulting in reproducible geometrical architectures. However, the design of the complex and intricate network of channels that are required in conventional CAD, is extremely time consuming: manually setting thousands of different geometrical parameters may require several days in which to design the individual scaffold structures. This research proposes an automated design methodology in order to overcome those limitations. The combined use of Object Oriented Programming and advanced CAD software, allows the rapid generation of thousands of different geometrical elements. Each has a different set of parameters that can be changed by the software, either randomly or according to a given mathematical formula, so that they match the different distribution of geometrical elements such as pore size and pore interconnectivity. This work describes a methodology that has been used to design five cubic scaffolds with pore size ranging from about 200 to 800 µm, each with an increased complexity of the internal geometry.Mechanical Engineerin

Three-Dimensional Spectral-Domain Optical Coherence Tomography Data Analysis for Glaucoma Detection

Purpose: To develop a new three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) data analysis method using a machine learning technique based on variable-size super pixel segmentation that efficiently utilizes full 3D dataset to improve the discrimination between early glaucomatous and healthy eyes. Methods: 192 eyes of 96 subjects (44 healthy, 59 glaucoma suspect and 89 glaucomatous eyes) were scanned with SD-OCT. Each SD-OCT cube dataset was first converted into 2D feature map based on retinal nerve fiber layer (RNFL) segmentation and then divided into various number of super pixels. Unlike the conventional super pixel having a fixed number of points, this newly developed variable-size super pixel is defined as a cluster of homogeneous adjacent pixels with variable size, shape and number. Features of super pixel map were extracted and used as inputs to machine classifier (LogitBoost adaptive boosting) to automatically identify diseased eyes. For discriminating performance assessment, area under the curve (AUC) of the receiver operating characteristics of the machine classifier outputs were compared with the conventional circumpapillary RNFL (cpRNFL) thickness measurements. Results: The super pixel analysis showed statistically significantly higher AUC than the cpRNFL (0.855 vs. 0.707, respectively, p = 0.031, Jackknife test) when glaucoma suspects were discriminated from healthy, while no significant difference was found when confirmed glaucoma eyes were discriminated from healthy eyes. Conclusions: A novel 3D OCT analysis technique performed at least as well as the cpRNFL in glaucoma discrimination and even better at glaucoma suspect discrimination. This new method has the potential to improve early detection of glaucomatous damage. © 2013 Xu et al

Efficient adaptive integration of functions with sharp gradients and cusps in n-dimensional parallelepipeds

In this paper, we study the efficient numerical integration of functions with sharp gradients and cusps. An adaptive integration algorithm is presented that systematically improves the accuracy of the integration of a set of functions. The algorithm is based on a divide and conquer strategy and is independent of the location of the sharp gradient or cusp. The error analysis reveals that for a $C^0$ function (derivative-discontinuity at a point), a rate of convergence of $n+1$ is obtained in $R^n$. Two applications of the adaptive integration scheme are studied. First, we use the adaptive quadratures for the integration of the regularized Heaviside function---a strongly localized function that is used for modeling sharp gradients. Then, the adaptive quadratures are employed in the enriched finite element solution of the all-electron Coulomb problem in crystalline diamond. The source term and enrichment functions of this problem have sharp gradients and cusps at the nuclei. We show that the optimal rate of convergence is obtained with only a marginal increase in the number of integration points with respect to the pure finite element solution with the same number of elements. The adaptive integration scheme is simple, robust, and directly applicable to any generalized finite element method employing enrichments with sharp local variations or cusps in $n$-dimensional parallelepiped elements.Comment: 22 page