Avaliação em 3D da cabeça da mandíbula em crianças portadoras de mordida cruzada posterior unilateral por meio de tomografia computadorizada de feixe cônico

Durante o desenvolvimento da oclusão, a instalação de maloclusões podem resultar em desarmonias dento faciais de natureza e severidade diversas, podendo provocar alterações no desenvolvimento crânio facial, dentre as estruturas envolvidas as Articulações Temporo Mandibulares (ATM), podem sofrer alguma influência, dessa forma a avaliação desta região, no aspecto morfológico e funcional, constituí tema de interesse, sempre que levados em conta os aspectos funcionais da oclusão. A relação entre a forma e a função, tanto das cabeças da mandíbula, bem como o contorno da fossa mandibular com as maloclusões ainda é controversa e não está compreendida por completo, porém a literatura sobre o assunto, demonstra correlação entre a instalação de maloclusões e modificações neste sistema, mesmo que algumas alterações não sejam de ordem estatística e em amostras de indivíduos em tenra idade, as mesmas podem comprometer o desenvolvimento adequado em indivíduos adultos ou mesmo adultos jovens. Tendo como propósito nesse estudo a avaliação das cabeças da mandíbula quanto ao volume e superficíe dos lados direito e esquerdo, cruzado e não cruzado, a amostra selecionada foi de 20 indivíduos com mordida cruzada posterior unilateral, com idades entre 06 e 09 anos de idade, utilizando imagens de tomografia computadorizada por feixe cônico, imagens obtidas por um equipamento modelo i- Cat, sendo utilizado na reformatação e manipulação das imagens o programa computacional - NemoCeph 3D® versão 11.5. Nas medições propostas para esse estudo, utilizou-se o teste t pareado de Student para amostras com distribuição normal. Na observação das tabelas e seus respectivos gráficos, podemos verificar que na comparação entre os lados direito e esquerdo, e cruzado e não cruzado das cabeças da mandíbula, com relação ao volume e superfície, existem diferenças numéricas entre elas, porém não pode ser observado diferenças estatísticas significantes, nessa amostra especifica com a metodologia empregada para esse estudo. Assim foi possível concluir que nas Mordidas Cruzadas Posteriores Unilaterais as cabeças da mandíbula tanto em seu volume como em sua superfície não apresentaram diferenças estatisticamente significantes na amostra estudada.

Condensados de Bose-Einstein em redes óticas: a transição superfluido-isolante de Mott em redes hexagonais e a classe de universalidade superfluido-vidro de Bose em 3D

Estudamos transições de fases quânticas em gases bosônicos ultrafrios aprisionados em redes óticas. A física desses sistemas é capturada por um modelo do tipo Bose-Hubbard que, no caso de um sistema sem desordem, em que os átomos têm interação de curto alcance e o tunelamento é apenas entre sítios primeiros vizinhos, prevê a transição de fases quântica superfluido-isolante de Mott (SF-MI) quando a profundidade do potencial da rede ótica é variado. Num primeiro estudo, verificamos como o diagrama de fases dessa transição muda quando passamos de uma rede quadrada para uma hexagonal. Num segundo, investigamos como a desordem modifica essa transição. No estudo com rede hexagonal, apresentamos o diagrama de fases da transição SF-MI e uma estimativa para o ponto crítico do primeiro lobo de Mott. Esses resultados foram obtidos usando o algoritmo de Monte Carlo quântico denominado Worm. Comparamos nossos resultados com os obtidos a partir de uma aproximação de campo médio e com os de um sistema com uma rede ótica quadrada. Ao introduzir desordem no sistema, uma nova fase emerge no diagrama de fases do estado fundamental intermediando a fase superfluida e a isolante de Mott. Essa nova fase é conhecida como vidro de Bose (BG) e a transição de fases quântica SF-BG que ocorre nesse sistema gerou muitas controvérsias desde seus primeiros estudos iniciados no fim dos anos 80. Apesar dos avanços em direção ao entendimento completo desta transição, a caracterização básica das suas propriedades críticas ainda é debatida. O que motivou nosso estudo, foi a publicação de resultados experimentais e numéricos em sistemas tridimensionais [Yu et al. Nature 489, 379 (2012), Yu et al. PRB 86, 134421 (2012)] que violam a lei de escala $\\phi= u z$, em que $\\phi$ é o expoente da temperatura crítica, $z$ é o expoente crítico dinâmico e $ u$ é o expoente do comprimento de correlação. Abordamos essa controvérsia numericamente fazendo uma análise de escalonamento finito usando o algoritmo Worm nas suas versões quântica e clássica. Nossos resultados demonstram que trabalhos anteriores sobre a dependência da temperatura de transição superfluido-líquido normal com o potencial químico (ou campo magnético, em sistemas de spin), $T_c \\propto (\\mu-\\mu_c)^\\phi$, estavam equivocados na interpretação de um comportamento transiente na aproximação da região crítica genuína. Quando os parâmetros do modelo são modificados de maneira a ampliar a região crítica quântica, simulações com ambos os modelos clássico e quântico revelam que a lei de escala $\\phi= u z$ [com $\\phi=2.7(2)$, $z=3$ e $ u = 0.88(5)$] é válida. Também estimamos o expoente crítico do parâmetro de ordem, encontrando $\\beta=1.5(2)$.

First Order Phase Transition in a 3D disordered system

We present a detailed numerical study on the effects of adding quenched impurities to a three dimensional system which in the pure case undergoes a strong first order phase transition (specifically, the ferromagnetic/paramagnetic transition of the site-diluted four states Potts model). We can state that the transition remains first-order in the presence of quenched disorder (a small amount of it) but it turns out to be second order as more impurities are added. A tricritical point, which is studied by means of Finite-Size Scaling, separates the first-order and second-order parts of the critical line. The results were made possible by a new definition of the disorder average that avoids the diverging-variance probability distributions that arise using the standard methodology. We also made use of a recently proposed microcanonical Monte Carlo method in which entropy, instead of free energy, is the basic quantity.

Diseño de un modelo geológico-geotécnico 3D de la Vega Baja del Río Segura (Alicante, SE España)

Los modelos geológico-geotécnicos permiten al ingeniero comprender mejor las condiciones reinantes en un determinado lugar, además de identificar los principales problemas geotécnicos y hacer más realista la estimación de propiedades del suelo. En este trabajo se presenta la metodología empleada para el diseño de un modelo geológico-geotécnico tridimensional de la Vega Baja del Río Segura que consta de cuatro zonas caracterizadas por sus propiedades geotécnicas y su problemática asociada. El modelo resulta fundamentalmente de gran utilidad para la planificación de investigaciones preliminares de obras civiles.

Detección automática con snakes y representación 3D sobre imágenes cerebrales

Comunicación presentada en la VI Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA'95), Alicante, 15-17 noviembre 1995.

GPGPU implementation of growing neural gas: application to 3D scene reconstruction

Self-organising neural models have the ability to provide a good representation of the input space. In particular the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time-consuming, especially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This paper proposes a Graphics Processing Unit (GPU) parallel implementation of the GNG with Compute Unified Device Architecture (CUDA). In contrast to existing algorithms, the proposed GPU implementation allows the acceleration of the learning process keeping a good quality of representation. Comparative experiments using iterative, parallel and hybrid implementations are carried out to demonstrate the effectiveness of CUDA implementation. The results show that GNG learning with the proposed implementation achieves a speed-up of 6× compared with the single-threaded CPU implementation. GPU implementation has also been applied to a real application with time constraints: acceleration of 3D scene reconstruction for egomotion, in order to validate the proposal.

3D-based reconstruction using growing neural gas landmark: application to rapid prototyping in shoe last manufacturing

Customizing shoe manufacturing is one of the great challenges in the footwear industry. It is a production model change where design adopts not only the main role, but also the main bottleneck. It is therefore necessary to accelerate this process by improving the accuracy of current methods. Rapid prototyping techniques are based on the reuse of manufactured footwear lasts so that they can be modified with CAD systems leading rapidly to new shoe models. In this work, we present a shoe last fast reconstruction method that fits current design and manufacturing processes. The method is based on the scanning of shoe last obtaining sections and establishing a fixed number of landmarks onto those sections to reconstruct the shoe last 3D surface. Automated landmark extraction is accomplished through the use of the self-organizing network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates up to 12 times the surface reconstruction and filtering processes used by the current shoe last design software. The proposed method offers higher accuracy compared with methods with similar efficiency as voxel grid.

3D Maps Representation Using GNG

Current RGB-D sensors provide a big amount of valuable information for mobile robotics tasks like 3D map reconstruction, but the storage and processing of the incremental data provided by the different sensors through time quickly become unmanageable. In this work, we focus on 3D maps representation and propose the use of the Growing Neural Gas (GNG) network as a model to represent 3D input data. GNG method is able to represent the input data with a desired amount of neurons or resolution while preserving the topology of the input space. Experiments show how GNG method yields a better input space adaptation than other state-of-the-art 3D map representation methods.

μ-MAR: Multiplane 3D Marker based Registration for depth-sensing cameras

Many applications including object reconstruction, robot guidance, and. scene mapping require the registration of multiple views from a scene to generate a complete geometric and appearance model of it. In real situations, transformations between views are unknown and it is necessary to apply expert inference to estimate them. In the last few years, the emergence of low-cost depth-sensing cameras has strengthened the research on this topic, motivating a plethora of new applications. Although they have enough resolution and accuracy for many applications, some situations may not be solved with general state-of-the-art registration methods due to the signal-to-noise ratio (SNR) and the resolution of the data provided. The problem of working with low SNR data, in general terms, may appear in any 3D system, then it is necessary to propose novel solutions in this aspect. In this paper, we propose a method, μ-MAR, able to both coarse and fine register sets of 3D points provided by low-cost depth-sensing cameras, despite it is not restricted to these sensors, into a common coordinate system. The method is able to overcome the noisy data problem by means of using a model-based solution of multiplane registration. Specifically, it iteratively registers 3D markers composed by multiple planes extracted from points of multiple views of the scene. As the markers and the object of interest are static in the scenario, the transformations obtained for the markers are applied to the object in order to reconstruct it. Experiments have been performed using synthetic and real data. The synthetic data allows a qualitative and quantitative evaluation by means of visual inspection and Hausdorff distance respectively. The real data experiments show the performance of the proposal using data acquired by a Primesense Carmine RGB-D sensor. The method has been compared to several state-of-the-art methods. The results show the good performance of the μ-MAR to register objects with high accuracy in presence of noisy data outperforming the existing methods.

Methodology based on registration techniques for representing subjects and their deformations acquired from general purpose 3D sensors

In this thesis a methodology for representing 3D subjects and their deformations in adverse situations is studied. The study is focused in providing methods based on registration techniques to improve the data in situations where the sensor is working in the limit of its sensitivity. In order to do this, it is proposed two methods to overcome the problems which can difficult the process in these conditions. First a rigid registration based on model registration is presented, where the model of 3D planar markers is used. This model is estimated using a proposed method which improves its quality by taking into account prior knowledge of the marker. To study the deformations, it is proposed a framework to combine multiple spaces in a non-rigid registration technique. This proposal improves the quality of the alignment with a more robust matching process that makes use of all available input data. Moreover, this framework allows the registration of multiple spaces simultaneously providing a more general technique. Concretely, it is instantiated using colour and location in the matching process for 3D location registration.

3D numerical modelling of acoustic horns using the method of fundamental solutions

In the present work, a three-dimensional (3D) formulation based on the method of fundamental solutions (MFS) is applied to the study of acoustic horns. The implemented model follows and extends previous works that only considered two-dimensional and axisymmetric horn configurations. The more realistic case of 3D acoustic horns with symmetry regarding two orthogonal planes is addressed. The use of the domain decomposition technique with two interconnected sub-regions along a continuity boundary is proposed, allowing for the computation of the sound pressure generated by an acoustic horn installed on a rigid screen. In order to reduce the model discretization requirements for these cases, Green’s functions derived with the image source methodology are adopted, automatically accounting for the presence of symmetry conditions. A strategy for the calculation of an optimal position of the virtual sources used by the MFS to define the solution is also used, leading to improved reliability and flexibility of the proposed method. The responses obtained by the developed model are compared to reference solutions, computed by well-established models based on the boundary element method. Additionally, numerically calculated acoustic parameters, such as directivity and beamwidth, are compared with those evaluated experimentally.

Evaluation of sampling method effects in 3D non-rigid registration

Since the beginning of 3D computer vision problems, the use of techniques to reduce the data to make it treatable preserving the important aspects of the scene has been necessary. Currently, with the new low-cost RGB-D sensors, which provide a stream of color and 3D data of approximately 30 frames per second, this is getting more relevance. Many applications make use of these sensors and need a preprocessing to downsample the data in order to either reduce the processing time or improve the data (e.g., reducing noise or enhancing the important features). In this paper, we present a comparison of different downsampling techniques which are based on different principles. Concretely, five different downsampling methods are included: a bilinear-based method, a normal-based, a color-based, a combination of the normal and color-based samplings, and a growing neural gas (GNG)-based approach. For the comparison, two different models have been used acquired with the Blensor software. Moreover, to evaluate the effect of the downsampling in a real application, a 3D non-rigid registration is performed with the data sampled. From the experimentation we can conclude that depending on the purpose of the application some kernels of the sampling methods can improve drastically the results. Bilinear- and GNG-based methods provide homogeneous point clouds, but color-based and normal-based provide datasets with higher density of points in areas with specific features. In the non-rigid application, if a color-based sampled point cloud is used, it is possible to properly register two datasets for cases where intensity data are relevant in the model and outperform the results if only a homogeneous sampling is used.

Integration of robotic inverse kinematic routines in an algorithmic 3D modeling software

An industrial manipulator equipped with an automatic clay extruder is used to realize a machine that can manufacture additively clay objects. The desired geometries are designed by means of a 3D modeling software and then sliced in a sequence of layers with the same thickness of the extruded clay section. The profiles of each layer are transformed in trajectories for the extruder and therefore for the end-effector of the manipulator. The goal of this thesis is to improve the algorithm for the inverse kinematic resolution and the integration of the routine within the development software that controls the machine (Rhino/Grasshopper). The kinematic model is described by homogeneous transformations, adopting the Denavit-Hartenberg standard convention. The function is implemented in C# and it has been preliminarily tested in Matlab. The outcome of this work is a substantial reduction of the computation time relative to the execution of the algorithm, which is halved.

Digital surface model, hillshade and orthophoto of the world's largest fossil oyster reef, links to GeoTIFFs

The world's largest fossil oyster reef, formed by the giant oyster Crassostrea gryphoides and located in Stetten (north of Vienna, Austria) is studied by Harzhauser et al., 2015, 2016; Djuricic et al., 2016. Digital documentation of the unique geological site is provided by terrestrial laser scanning (TLS) at the millimeter scale. Obtaining meaningful results is not merely a matter of data acquisition with a suitable device; it requires proper planning, data management, and postprocessing. Terrestrial laser scanning technology has a high potential for providing precise 3D mapping that serves as the basis for automatic object detection in different scenarios; however, it faces challenges in the presence of large amounts of data and the irregular geometry of an oyster reef. We provide a detailed description of the techniques and strategy used for data collection and processing in Djuricic et al., 2016. The use of laser scanning provided the ability to measure surface points of 46,840 (estimated) shells. They are up to 60-cm-long oyster specimens, and their surfaces are modeled with a high accuracy of 1 mm. In addition to laser scanning measurements, more than 300 photographs were captured, and an orthophoto mosaic was generated with a ground sampling distance (GSD) of 0.5 mm. This high-resolution 3D information and the photographic texture serve as the basis for ongoing and future geological and paleontological analyses. Moreover, they provide unprecedented documentation for conservation issues at a unique natural heritage site.