Multi-resolution Model Research Articles

Automatic multi-resolution shape modeling of multi-organ structures.

Point Distribution Models (PDM) are among the most popular shape description techniques and their usefulness has been demonstrated in a wide variety of medical imaging applications. However, to adequately characterize the underlying modeled population it is essential to have a representative number of training samples, which is not always possible. This problem is especially relevant as the complexity of the modeled structure increases, being the modeling of ensembles of multiple 3D organs one of the most challenging cases. In this paper, we introduce a new GEneralized Multi-resolution PDM (GEM-PDM) in the context of multi-organ analysis able to efficiently characterize the different inter-object relations, as well as the particular locality of each object separately. Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller anatomically significant regions within organs. The significant advantage of the GEM-PDM method over two previous approaches (PDM and hierarchical PDM) in terms of shape modeling accuracy and robustness to noise, has been successfully verified for two different databases of sets of multiple organs: six subcortical brain structures, and seven abdominal organs. Finally, we propose the integration of the new shape modeling framework into an active shape-model-based segmentation algorithm. The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.

A Multiresolution Gaussian Process Model for the Analysis of Large Spatial Datasets

We develop a multiresolution model to predict two-dimensional spatial fields based on irregularly spaced observations. The radial basis functions at each level of resolution are constructed using a Wendland compactly supported correlation function with the nodes arranged on a rectangular grid. The grid at each finer level increases by a factor of two and the basis functions are scaled to have a constant overlap. The coefficients associated with the basis functions at each level of resolution are distributed according to a Gaussian Markov random field (GMRF) and take advantage of the fact that the basis is organized as a lattice. Several numerical examples and analytical results establish that this scheme gives a good approximation to standard covariance functions such as the Matérn and also has flexibility to fit more complicated shapes. The other important feature of this model is that it can be applied to statistical inference for large spatial datasets because key matrices in the computations are sparse. The computational efficiency applies to both the evaluation of the likelihood and spatial predictions.

Maximum penetration level of distributed generation in consideration of voltage fluctuations based on multi‐resolution model

To maintain the safe and stable operation of power system with the interconnection of distributed generation (DG), the urgent need arises to determine the maximum penetration level of DG. Voltage fluctuation, which is especially affected by the stochastic nature of renewable generation and load, has a significant impact on DG penetration. Thus in this study a two-dimensional multi-resolution model, which can demonstrate the impact of renewable generation and load on voltage fluctuation, is proposed. Then an analytical methodology based on the proposed model is presented to determine the maximum penetration level, without violating the limits of voltage fluctuation. Finally, all of them are applied to the IEEE 34 node test feeder, and simulation results show that the maximum penetration level will be lower if the stochastic variations of DG and load are more severe. Therefore the proposed method is a useful solution to the determination of DG penetration, and the multi-resolution model can greatly simplify the process of calculating and analysing.

Adaptive Boundaries in Multi-Resolution Simulations

Biomolecular simulations generally require a compromise between forcefield resolution and computational efficiency. Methods that combine multiple levels of resolution promise to extend the ability of simulations to handle bigger systems and more complex processes.We have developed an explicit/continuum solvent model that is able to reproduce the effects of explicit biomolecular solvation while only including a fraction of the molecules that would otherwise be required. We are extending this approach as a general multi-resolution model where both solvent and other, more complex, molecules change representation as they move across the boundaries of the explicit and continuum domains.This model includes: (1) new boundary methods that accurately reproduce thermodynamic and kinetic properties in the explicit region exactly, within statistical error, as if they were taken from large, fully explicit simulations; (2) adaptive boundaries that spatially alter the level of detail in response to an evolving molecular environment; and (3) a grand canonical control of molecular components, relaxing the density of chemical species as the simulation progresses (important for studies in crystallization, assembly, etc.).Our current work is aimed at surmounting a considerable challenge facing all multi-resolution models: transferability to new systems and arbitrary geometries. Overcoming this challenge will be essential in making these multi-resolution models ready to be used ‘out of the box’ for a range of problems in biophysics.

Design of Porous Micro-Structures Using Curvature Analysis for Additive-Manufacturing

The emerging field of additive manufacturing with bio-compatible materials has led to personalized design of porous micro-structures used in healthcare. Complex micro-structures are characterized by freeform surfaces and spatially varying porosity. Currently, there is no CAD system that can handle the design of micro-structures due to their high complexity. This paper describes a direct expansion of our research on generating 3D adaptive models of porous micro-structures. Using this approach, a designer can either manually select a Region of Interest (ROI), or define a curvature based criterion for selecting ROI while defining its level of detail. In the proposed approach, the multi-resolution volumetric model is based on designing a customized model, composed of the following stages (a) Reconstructing a multi-resolution volumetric model of a porous structure; (b) Defining ROIs and their resolution properties; and (c) Constructing an adaptive model. The feasibility of the proposed method is demonstrated on 3D models of porous micro-structures. These models are characterized by a large amount of detail and geometrical complexity. The proposed method has been applied on bone models that were reconstructed from micro-CT images. The proposed approach facilitates the porous characteristic and enables local reduction of the model complexity while optimizing the accuracy. For additive manufacturing application, the approach can be used for designing a porous micro-structure with reduced material volume while eliminating irrelevant geometric features.

A hierarchical method for coupling analysis of design services in distributed collaborative design environment

Design is a kind of highly complex activities with a large number of coupling relationships existing among essential design factors and design resources. This paper investigates the approach and mechanism of distributed design resources integration and binding in collaborative design process based on service-oriented architecture. A SORCER-based collaborative design environment is presented. An essential design factors matrix is designed as the binding mechanism to drive distributed design resources integration process during the design tasks execution time. Then, a coupling analysis method for design service modelling and execution is proposed. In order to build a multi-resolution coupling model in the local and global size, an essential design factors binding matrix and an essential design factors matrix group are adopted to express the internal relationships between design services. A hybrid approach, based on the partitioning operation, clustering operation and the genetic algorithm, are used to solve the coupling sets for global essential design factors.

Integration of 3D modeling, aerial LiDAR and photogrammetry to study a synsedimentary structure in the Early Jurassic Calcari Grigi (Southern Alps, Italy)

LiDAR and photogrammetry data are integrated to study an Early Jurassic extensional synsedimentary structure in the Italian Southern Alps. Airborne LiDAR data helped in getting geologic information in areas covered by vegetation, photogrammetry was applied to produce a high-resolution 3D textured model of the inaccessible parts of the outcrop. LiDAR and photgrammetric data were merged together producing a multi-resolution model. Key geologic boundaries and faults bounding the synsedimentary structure were digitized in a 3D geomodeling environment. The reconstruction yielded information about the structure kinematics and accumulated displacements.

Design of optimal ecosystem monitoring networks: hotspot detection and biodiversity patterns

Effective monitoring of ecosystems is crucial for assessing and possibly anticipating shifts, quantifying ecosystem services, and optimal decision making based on shifts and services. The selection of monitoring sites is typically suboptimal following local stakeholder or research interests that do not allow to capture ecosystem patterns and dynamics as a whole. The design of optimal monitoring network is crucial for the accurate determination of biodiversity patterns of ecosystems. A novel model for the design of optimal monitoring networks for biodiversity based on the concept of the value of information (VoI) is proposed. The VoI is assigned to species richness that is the economically and ecologically valuable metric. As a case study the trinational frontier ecosystem among Brazil, Peru, and Bolivia is considered for the model. A multiresolution texture-based model estimates species richness and turnover on satellite imagery calibrated on different sets of information coming from forest plot data organized in network topologies. The optimal monitoring network is the network that minimizes the integrated VoI defined as the variation of the VoI in the 28 years considered. This is equivalent to minimize the sum of the species turnover of the ecosystem. The small world network is identified as the optimal and most resilient monitoring network whose nodes are the hotspots of species richness. The hotspots are identified as the sites whose VoI is the highest for the whole period considered. Hence, the hotspots are the most valuable communities for inferring biodiversity patterns and the most ecologically/economically valuable according to the richness—resilience hypothesis. Most hotspots are honored by the small world network that can be thought as the ”backbone” ecological network of the ecosystem. The small world monitoring network has an accuracy ~50 % higher than other network topologies in predicting biodiversity patterns. This network has the highest VoI at any time step and scale considered; thus, it guarantees to track changes of ecosystems in space and time. The network that results from the optimal trade-off between data value with their uncertainty and relevance, has deep implications for understanding ecosystem function and for management decisions. The model allows to include preferences for ecosystem communities by using differential weights on the VoI of these communities, and economic constraints that limit the extension of the network. Because of the optimal integration of environmental, social, and economical factors the model allows a sustainable monitoring and planning of biodiversity for the future.

Multi-scale hybrid models for radiopharmaceutical dosimetry with Geant4

The accuracy of radiopharmaceutical absorbed dose distributions computed through Monte Carlo (MC) simulations is mostly limited by the low spatial resolution of 3D imaging techniques used to define the simulation geometry. This issue also persists with the implementation of realistic hybrid models built using polygonal mesh and/or NURBS as they require to be simulated in their voxel form in order to reduce computation times. The existing trade-off between voxel size and simulation speed leads on one side, in an overestimation of the size of small radiosensitive structures such as the skin or hollow organs walls and, on the other, to unnecessarily detailed voxelization of large, homogeneous structures.We developed a set of computational tools based on VTK and Geant4 in order to build multi-resolution organ models. Our aim is to use different voxel sizes to represent anatomical regions of different clinical relevance: the MC implementation of these models is expected to improve spatial resolution in specific anatomical structures without significantly affecting simulation speed. Here we present the tools developed through a proof of principle example. Our approach is validated against the standard Geant4 technique for the simulation of voxel geometries.

A Flexible Multi-Resolution Modeling Method of SoS Combat

A solution to improve the flexibility of simulation under the circumstance of SoS (System-of-Systems) combat has been provided in this paper. A CAS (Complex Adaptive System) based modeling method is used in this method after analyzing the military multi-layer architecture and surveying the modeling method, by joining CAS and MRM(Multi-Resolution Modeling), a military system is modeled in several resolution and some key technology are probed into and discussed in this paper. The analysis results show that method has great current significance and reference value for modeling combat system.

A Digital Watermarking Algorithm Based on Wavelet Transform

Digital watermarking is a new information security technology, and it uses the information to protect the security of multimedia data hiding technique. Digital watermarking in wavelet domain can make effective use of the human visual system characteristics, and can be compatible with the international compression standard, and the embedding watermark signal energy can be distributed to all of the pixel space. Based on the characteristic of multi-resolution wavelet decomposition and human visual system model matching, digital watermarking algorithm based on wavelet transform is proposed in this paper. The algorithm for tamper proof is designed by quantifying the significant wavelet coefficients to embed watermark sequence. Preprocessing and quantifying the image of this algorithm are studied, which resolves the rounding error and overflow problem brought by the watermarked image pixel values of wavelet transform. Through various attack test and analysis, the experimentation shows that it has strong robustness, can resist many common image attacks, and has strong practicability.

Multi-Resolution WNN Fault Diagnosis Model Based on Unscented Kalman Filtering for Rotating Machinery

BP neural network has a good nonlinear mapping ability, and can describe the relationship between frequency characteristics and fault. However, the multi-resolution wavelet neural network has the simple learning rules, fast training speed with the avoidance of local minima. So a multi-resolution wavelet neural network based on UKF is proposed to solve the problem of fault diagnosis for rotating machinery. The simulation result shows that the proposed multi-resolution wavelet neural network based on UKF value has a good diagnosis capability, and is better than that of traditional BP neural network and wavelet neural network.

Unified global and regional wave model on a multi-resolution grid

Models for ocean surface wave forecasting in weather centres comprise global and regional systems in order to efficiently meet service demands. Regional models cannot run alone and have to use large area or global models to provide boundary wave spectra. The modern two-way nesting technique is to run the two models together with the regional model domain covered by both resolutions. An alternative method is to use a single multi-resolution grid that fits irregular coastlines and provides refined resolutions in selected regions. This paper presents a multi-resolution model based on a spherical multiple-cell (SMC) grid, which is designed to relax the CFL restriction of Eulerian advection time step at high latitudes by merging the conventional latitude-longitude grid cells. The implementation of the SMC grid in WAVEWATCH III is described, and a multi-resolution (6, 12 and 25 km) global SMC configuration is compared with a suite of nested grid ocean surface wave models, including 35-km global, 8-km European and 4-km UK regional models. Verification against buoy and platform wave observations indicates that the unified model is better than the 35-km global and very close in performance to the two regional models.

Ocean dynamics and numerical modeling of canyons and shelfbreaks

Multiscale ocean dynamics and multi-resolution numerical modeling of canyons and shelfbreaks are outlined. The dynamics focus is on fronts, currents, tides, and internal tides/waves that occur in these regions. Due to the topographic gradients and strong internal field gradients, nonlinear terms and non-hydrostatic dynamics can be significant. Computationally, a challenge is to achieve accurate simulations that resolve strong gradients over dynamically significant space- and time-scales. To do so, one component are high-order schemes that are more accurate for the same efficiency than lower-order schemes. A second is multi-resolution grids that allow optimized refinements, such as reducing errors near steep topography. A third are methods that allow to solve for multiple dynamics, e.g., hydrostatic and non-hydrostatic, seamlessly. To address these components, new hybridizable discontinuous Galerkin (HDG) finite-element schemes for (non)-hydrostatic physics including a nonlinear free-surface are introduced. The results of data-assimilative multi-resolution simulations are then discussed, using the primitive-equation MSEAS system and telescoping implicitly two-way nested domains. They correspond to collaborative experiments: (i) Shallow Water 06 (SW06) and the Integrated Ocean Dynamics and Acoustics (IODA) research in the Middle Atlantic Bight region; (ii) Quantifying, Predicting and Exploiting Uncertainty (QPE) in the Taiwan-Kuroshio region; and (iii) Philippines Straits Dynamics Experiment (PhilEx).

Towards multi-resolution global climate modeling with ECHAM6–FESOM. Part I: model formulation and mean climate

A new climate model has been developed that employs a multi-resolution dynamical core for the sea ice-ocean component. In principle, the multi-resolution approach allows one to use enhanced horizontal resolution in dynamically active regions while keeping a coarse-resolution setup otherwise. The coupled model consists of the atmospheric model ECHAM6 and the finite element sea ice-ocean model (FESOM). In this study only moderate refinement of the unstructured ocean grid is applied and the resolution varies from about 25 km in the northern North Atlantic and in the tropics to about 150 km in parts of the open ocean; the results serve as a benchmark upon which future versions that exploit the potential of variable resolution can be built. Details of the formulation of the model are given and its performance in simulating observed aspects of the mean climate is described. Overall, it is found that ECHAM6–FESOM realistically simulates many aspects of the observed climate. More specifically it is found that ECHAM6–FESOM performs at least as well as some of the most sophisticated climate models participating in the fifth phase of the Coupled Model Intercomparison Project. ECHAM6–FESOM shares substantial shortcomings with other climate models when it comes to simulating the North Atlantic circulation.

Multi-resolution voxel phantom modeling: a high-resolution eye model for computational dosimetry

Voxel models of the human body are commonly used for simulating radiation dose with a Monte Carlo radiation transport code. Due to memory limitations, the voxel resolution of these computational phantoms is typically too large to accurately represent the dimensions of small features such as the eye. Recently reduced recommended dose limits to the lens of the eye, which is a radiosensitive tissue with a significant concern for cataract formation, has lent increased importance to understanding the dose to this tissue. A high-resolution eye model is constructed using physiological data for the dimensions of radiosensitive tissues, and combined with an existing set of whole-body models to form a multi-resolution voxel phantom, which is used with the MCNPX code to calculate radiation dose from various exposure types. This phantom provides an accurate representation of the radiation transport through the structures of the eye. Two alternate methods of including a high-resolution eye model within an existing whole-body model are developed. The accuracy and performance of each method is compared against existing computational phantoms.

Rainfall data analyzing using moving average (MA) model and wavelet multi-resolution intelligent model for noise evaluation to improve the forecasting accuracy

Rainfall forecasting and approximation of its magnitude have a huge and imperative role in water management and runoff forecasting. The main objective of this paper is to obtain the relationship between rainfall time series achieved from wavelet transform (WT) and moving average (MA) in Klang River basin, Malaysia. For this purpose, the Haar and Dmey WTs were applied to decompose the rainfall time series into 7, 10 different resolution levels, respectively. Several preprocessing case studies based on 2-, 3-, 5-, 10-, 15-, 20-, 25-, and 30-month MAs were carried out to discover a longer-term trend compared to a shorter-term MA. The information and data were gathered from Klang Gates Dam, Malaysia, from 1997 to 2008. Regarding the behavior, the time series of 10-, 15-, 20-, and 30-day rainfall are decomposed into approximation and details coefficient with different kind of WT. Correlation coefficient R 2 and root-mean-square error criteria are applied to examine the performance of the models. The results show that there are some similarities between MA filters and wavelet approximation sub-series filters due to noise elimination. Moreover, the results obtained that the high correlation with MAs can be achieved via Dmey WT compared to Haar wavelet for rainfall data. Moreover, clean signals could be used as model inputs to improve the model performance. Therefore, signal decomposition techniques for the purpose of data preprocessing could be favorable and could be appropriate for elimination of the errors.

Automated construction of the boundaries of basin geosystems for the Volga Federal District

Using the Volga (Privolzhskii) Federal District as an example, we offer the solution of such a currently central scientific and methodological problem as automated identification of the boundaries of basin geosystems under different landscape and geomorphological conditions in terms of multiresolution digital elevation models. The main stages of work are described, namely the development of the digital elevation model, its hydrological adjustment, identification of the boundaries of basin geosystems, and validity assessment of results obtained. The technique has been developed for constructing a hydrologically valid digital elevation model with the purpose of identifying the boundaries of basin geosystems.

Image-fusion-based multi-resolution active contour model

This paper proposes an active contour model (snake) based on image fusion, which is used in object detection and object tracking. Firstly, a multi-resolution image fusion with wavelet transform is applied to obtain the multi-resolution fused images. Secondly, in the low-frequency sub-image, a snake is applied with the Sobel operator to detect the object's contour; and in other high-frequency sub-images, a wavelet-based snake is applied. The two convergent snakes are fused in a multi-resolution scheme to obtain a fused snake in the fused image in an original resolution. Experiment results indicate this fused snake's detection or tracking accuracy is improved greatly.

Web-based Visualization and Query of semantically segmented multiresolution 3D Models in the Field of Cultural Heritage

Abstract. Many important Cultural Heritage sites have been studied over long periods of time by different means of technical equipment, methods and intentions by different researchers. This has led to huge amounts of heterogeneous "traditional" datasets and formats. The rising popularity of 3D models in the field of Cultural Heritage in recent years has brought additional data formats and makes it even more necessary to find solutions to manage, publish and study these data in an integrated way. The MayaArch3D project aims to realize such an integrative approach by establishing a web-based research platform bringing spatial and non-spatial databases together and providing visualization and analysis tools. Especially the 3D components of the platform use hierarchical segmentation concepts to structure the data and to perform queries on semantic entities. This paper presents a database schema to organize not only segmented models but also different Levels-of-Details and other representations of the same entity. It is further implemented in a spatial database which allows the storing of georeferenced 3D data. This enables organization and queries by semantic, geometric and spatial properties. As service for the delivery of the segmented models a standardization candidate of the OpenGeospatialConsortium (OGC), the Web3DService (W3DS) has been extended to cope with the new database schema and deliver a web friendly format for WebGL rendering. Finally a generic user interface is presented which uses the segments as navigation metaphor to browse and query the semantic segmentation levels and retrieve information from an external database of the German Archaeological Institute (DAI).