914 resultados para 3D Model
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We present a new algorithm to compute the voxel-wise genetic contribution to brain fiber microstructure using diffusion tensor imaging (DTI) in a dataset of 25 monozygotic (MZ) twins and 25 dizygotic (DZ) twin pairs (100 subjects total). First, the structural and DT scans were linearly co-registered. Structural MR scans were nonlinearly mapped via a 3D fluid transformation to a geometrically centered mean template, and the deformation fields were applied to the DTI volumes. After tensor re-orientation to realign them to the anatomy, we computed several scalar and multivariate DT-derived measures including the geodesic anisotropy (GA), the tensor eigenvalues and the full diffusion tensors. A covariance-weighted distance was measured between twins in the Log-Euclidean framework [2], and used as input to a maximum-likelihood based algorithm to compute the contributions from genetics (A), common environmental factors (C) and unique environmental ones (E) to fiber architecture. Quanititative genetic studies can take advantage of the full information in the diffusion tensor, using covariance weighted distances and statistics on the tensor manifold.
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The 3D Water Chemistry Atlas is an intuitive, open source, Web-based system that enables the three-dimensional (3D) sub-surface visualization of ground water monitoring data, overlaid on the local geological model (formation and aquifer strata). This paper firstly describes the results of evaluating existing virtual globe technologies, which led to the decision to use the Cesium open source WebGL Virtual Globe and Map Engine as the underlying platform. Next it describes the backend database and search, filtering, browse and analysis tools that were developed to enable users to interactively explore the groundwater monitoring data and interpret it spatially and temporally relative to the local geological formations and aquifers via the Cesium interface. The result is an integrated 3D visualization system that enables environmental managers and regulators to assess groundwater conditions, identify inconsistencies in the data, manage impacts and risks and make more informed decisions about coal seam gas extraction, waste water extraction, and water reuse.
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This study used the specific example of 3D printing with acrylonitrile butadiene styrene (ABS) as a means to investigate the potential usefulness of benchtop rapid prototyping as a technique for producing patient specific phantoms for radiotherapy dosimetry. Three small cylinders and one model of a human lung were produced via in-house 3D printing with ABS, using 90%, 50%, 30% and 10% ABS infill densities. These phantom samples were evaluated in terms of their geometric accuracy, tissue equivalence and radiation hardness, when irradiated using a range of clinical radiotherapy beams. The measured dimensions of the small cylindrical phantoms all matched their planned dimensions, within 1mm. The lung phantom was less accurately matched to the lung geometry on which it was based, due to simplifications introduced during the phantom design process. The mass densities, electron densities and linear attenuation coefficients identified using CT data, as well as the results of film measurements made using megavoltage photon and electron beams, indicated that phantoms printed with ABS, using infill densities of 30% or more, are potentially useful as lung- and tissue-equivalent phantoms for patient-specific radiotherapy dosimetry. All cylindrical 3D printed phantom samples were found to be unaffected by prolonged radiation and to accurately match their design specifications. However, care should be taken to avoid oversimplifying anatomical structures when printing more complex phantoms.
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Reconstructing 3D motion data is highly under-constrained due to several common sources of data loss during measurement, such as projection, occlusion, or miscorrespondence. We present a statistical model of 3D motion data, based on the Kronecker structure of the spatiotemporal covariance of natural motion, as a prior on 3D motion. This prior is expressed as a matrix normal distribution, composed of separable and compact row and column covariances. We relate the marginals of the distribution to the shape, trajectory, and shape-trajectory models of prior art. When the marginal shape distribution is not available from training data, we show how placing a hierarchical prior over shapes results in a convex MAP solution in terms of the trace-norm. The matrix normal distribution, fit to a single sequence, outperforms state-of-the-art methods at reconstructing 3D motion data in the presence of significant data loss, while providing covariance estimates of the imputed points.
Resumo:
Background The Circle of Willis (CoW) is the most important collateral pathway of the cerebral artery. The present study aims to investigate the collateral capacity of CoW with anatomical variation when unilateral internalcarotid artery (ICA) is occluded. Methods Basing on MRI data, we have reconstructed eight 3D models with variations in the posterior circulation of the CoW and set four different degrees of stenosis in the right ICA, namely 24%, 43%, 64% and 79%, respectively. Finally, a total of 40 models are performed with computational fluid dynamics simulations. All of the simulations share the same boundary condition with static pressure and the volume flow rate (VFR) are obtained to evaluate their collateral capacity. Results As for the middle cerebral artery (MCA) and the anterior cerebral artery (ACA), the transitional-type model possesses the best collateral capacity. But for the posterior cerebral artery (PCA), unilateral stenosis of ICA has the weakest influence on the unilateral posterior communicating artery (PCoA) absent model. We also find that the full fetal-type posterior circle of Willis is an utmost dangerous variation which must be paid more attention. Conclusion The results demonstrate that different models have different collateral capacities in coping stenosis of unilateral ICA and these differences can be reflected by different outlets. The study could be used as a reference for neurosurgeon in choosing the best treatment strategy.
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A three-dimensional (3D) mathematical model of tumour growth at the avascular phase and vessel remodelling in host tissues is proposed with emphasis on the study of the interactions of tumour growth and hypoxic micro-environment in host tissues. The hybrid based model includes the continuum part, such as the distributions of oxygen and vascular endothelial growth factors (VEGFs), and the discrete part of tumour cells (TCs) and blood vessel networks. The simulation shows the dynamic process of avascular tumour growth from a few initial cells to an equilibrium state with varied vessel networks. After a phase of rapidly increasing numbers of the TCs, more and more host vessels collapse due to the stress caused by the growing tumour. In addition, the consumption of oxygen expands with the enlarged tumour region. The study also discusses the effects of certain factors on tumour growth, including the density and configuration of preexisting vessel networks and the blood oxygen content. The model enables us to examine the relationship between early tumour growth and hypoxic micro-environment in host tissues, which can be useful for further applications, such as tumour metastasis and the initialization of tumour angiogenesis.
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Light interception is a major factor influencing plant development and biomass production. Several methods have been proposed to determine this variable, but its calculation remains difficult in artificial environments with heterogeneous light. We propose a method that uses 3D virtual plant modelling and directional light characterisation to estimate light interception in highly heterogeneous light environments such as growth chambers and glasshouses. Intercepted light was estimated by coupling an architectural model and a light model for different genotypes of the rosette species Arabidopsis thaliana (L.) Heynh and a sunflower crop. The model was applied to plants of contrasting architectures, cultivated in isolation or in canopy, in natural or artificial environments, and under contrasting light conditions. The model gave satisfactory results when compared with observed data and enabled calculation of light interception in situations where direct measurements or classical methods were inefficient, such as young crops, isolated plants or artificial conditions. Furthermore, the model revealed that A. thaliana increased its light interception efficiency when shaded. To conclude, the method can be used to calculate intercepted light at organ, plant and plot levels, in natural and artificial environments, and should be useful in the investigation of genotype-environment interactions for plant architecture and light interception efficiency. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.
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Three-dimensional QSAR studies for N-4-arylacryloylpiperazin-1-yl-phenyl-oxazolidinones were conducted using TSAR 3.3. The in vitro activities (MICs) of the compounds against Staphylococcus aureus ATCC 25923 exhibited a strong correlation with the prediction made by the model developed in the present study.
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Three-dimensional QSAR studies for substituted aryloxazolidinones 3–9 were conducted using TSAR 3.3. The in vitro activities (MICs) of the compounds against Staphylococcus aureus and Enterococcus faecalis exhibited a good correlation with the prediction made by the model using heat of formation and LUMO energies.
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A nonlinear suboptimal guidance scheme is developed for the reentry phase of the reusable launch vehicles. A recently developed methodology, named as model predictive static programming (MPSP), is implemented which combines the philosophies of nonlinear model predictive control theory and approximate dynamic programming. This technique provides a finite time nonlinear suboptimal guidance law which leads to a rapid solution of the guidance history update. It does not have to suffer from computational difficulties and can be implemented online. The system dynamics is propagated through the flight corridor to the end of the reentry phase considering energy as independent variable and angle of attack as the active control variable. All the terminal constraints are satisfied. Among the path constraints, the normal load is found to be very constrictive. Hence, an extra effort has been made to keep the normal load within a specified limit and monitoring its sensitivity to the perturbation.
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We address the issue of rate-distortion (R/D) performance optimality of the recently proposed switched split vector quantization (SSVQ) method. The distribution of the source is modeled using Gaussian mixture density and thus, the non-parametric SSVQ is analyzed in a parametric model based framework for achieving optimum R/D performance. Using high rate quantization theory, we derive the optimum bit allocation formulae for the intra-cluster split vector quantizer (SVQ) and the inter-cluster switching. For the wide-band speech line spectrum frequency (LSF) parameter quantization, it is shown that the Gaussian mixture model (GMM) based parametric SSVQ method provides 1 bit/vector advantage over the non-parametric SSVQ method.
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This paper presents a detailed analysis of a model for military conflicts where the defending forces have to determine an optimal partitioning of available resources to counter attacks from an adversary in two different fronts in an area fire situation. Lanchester linear law attrition model is used to develop the dynamical equations governing the variation in force strength. Here we address a static resource allocation problem namely, Time-Zero-Allocation (TZA) where the resource allocation is done only at the initial time. Numerical examples are given to support the analytical results.
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Interactions between tumour cells and extracellular matrix proteins of the tumour microenvironment play crucial roles in cancer progression. So far, however, there are only a few experimental platforms available that allow us to study these interactions systematically in a mechanically defined three-dimensional (3D) context. Here, we have studied the effect of integrin binding motifs found within common extracellular matrix (ECM) proteins on 3D breast (MCF-7) and prostate (PC-3, LNCaP) cancer cell cultures, and co-cultures with endothelial and mesenchymal stromal cells. For this purpose, matrix metalloproteinase-degradable biohybrid poly(ethylene) glycol-heparin hydrogels were decorated with the peptide motifs RGD, GFOGER (collagen I), or IKVAV (laminin-111). Over 14 days, cancer spheroids of 100-200µm formed. While the morphology of poorly invasive MCF-7 and LNCaP cells was not modulated by any of the peptide motifs, the aggressive PC-3 cells exhibited an invasive morphology when cultured in hydrogels comprising IKVAV and GFOGER motifs compared to RGD motifs or nonfunctionalised controls. PC-3 (but not MCF-7 and LNCaP) cell growth and endothelial cell infiltration were also significantly enhanced in IKVAV and GFOGER presenting gels. Taken together, we have established a 3D culture model that allows for dissecting the effect of biochemical cues on processes relevant to early cancer progression. These findings provide a basis for more mechanistic studies that may further advance our understanding of how ECM modulates cancer cell invasion and how to ultimately interfere with this process.
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This paper describes the 3D Water Chemistry Atlas - an open source, Web-based system that enables the three-dimensional (3D) sub-surface visualization of ground water monitoring data, overlaid on the local geological model. Following a review of existing technologies, the system adopts Cesium (an open source Web-based 3D mapping and visualization interface) together with a PostGreSQL/PostGIS database, for the technical architecture. In addition a range of the search, filtering, browse and analysis tools were developed that enable users to interactively explore the groundwater monitoring data and interpret it spatially and temporally relative to the local geological formations and aquifers via the Cesium interface. The result is an integrated 3D visualization system that enables environmental managers and regulators to assess groundwater conditions, identify inconsistencies in the data, manage impacts and risks and make more informed decisions about activities such as coal seam gas extraction, waste water extraction and re-use.
Resumo:
This paper presents an algorithm for solid model reconstruction from 2D sectional views based on volume-based approach. None of the existing work in automatic reconstruction from 2D orthographic views have addressed sectional views in detail. It is believed that the volume-based approach is better suited to handle different types of sectional views. The volume-based approach constructs the 3D solid by a boolean combination of elementary solids. The elementary solids are formed by sweep operation on loops identified in the input views. The only adjustment to be made for the presence of sectional views is in the identification of loops that would form the elemental solids. In the algorithm, the conventions of engineering drawing for sectional views, are used to identify the loops correctly. The algorithm is simple and intuitive in nature. Results have been obtained for full sections, offset sections and half sections. Future work will address other types of sectional views such as removed and revolved sections and broken-out sections. (C) 2004 Elsevier Ltd. All rights reserved.