Image processing based three-dimensional model reconstruction for cross-platform numerical simulation

Numerical simulation is the most powerful computational and analysis tool for a large variety of engineering and physical problems.For a complex problem relating to multi-field,multi-process and multi-scale,different computing tools have to be developed so as to solve particular fields at different scales and for different processes.Therefore,the integration of different types of software is inevitable.However,it is difficult to perform the transfer of the meshes and simulated results among software packages because of the lack of shared data formats or encrypted data formats.An image processing based method for three-dimensional model reconstruction for numerical simulation was proposed,which presents a solution to the integration problem by a series of slice or projection images obtained by the post-processing modules of the numerical simulation software.By means of mapping image pixels to meshes of either finite difference or finite element models,the geometry contour can be extracted to export the stereolithography model.The values of results,represented by color,can be deduced and assigned to the meshes.All the models with data can be directly or indirectly integrated into other software as a continued or new numerical simulation.The three-dimensional reconstruction method has been validated in numerical simulation of castings and case studies were provided in this study.

Three-Dimensional Model Reconstruction of Nonwovens from Multi-Focus Images

The three-dimensional(3D)model is of great significance to analyze the performance of nonwovens.However,the existing modelling methods could not reconstruct the 3D structure of nonwovens at low cost.A new method based on deep learning was proposed to reconstruct 3D models of nonwovens from multi-focus images.A convolutional neural network was trained to extract clear fibers from sequence images.Image processing algorithms were used to obtain the radius,the central axis,and depth information of fibers from the extraction results.Based on this information,3D models were built in 3D space.Furthermore,self-developed algorithms optimized the central axis and depth of fibers,which made fibers more realistic and continuous.The method with lower cost could reconstruct 3D models of nonwovens conveniently.

Model reconstruction for worn blades based on hybrid surface registrations

Model reconstruction is crucial in blade repair because it directly determines the shape precision and finish of a repaired surface.However,owing to insufficient surface data pertaining to defective regions and the unique deformation caused by harsh environments,modeling a worn blade remains difficult.Hence,a model reconstruction method for worn blades is developed in this study.Unlike conventional methods of constructing and interpolating sectional curves,the proposed method focuses on modifying a nominal computer aided design(CAD)model to reconstruct the worn blade.Through weighted rigid registration and constraint-based non-rigid registration,the design surface extracted from the nominal CAD model can be deformed to align with the surface data of the worn blade without a significant loss of its initial shape.Verification results show that the deformed design surface exhibits sufficient smoothness and accuracy for guiding tool path generation in the subsequent blade repair.

Preoperative 3D reconstruction and fluorescent indocyanine green for laparoscopic duodenum preserving pancreatic head resection:A case report

BACKGROUND Duodenum-preserving pancreatic head resection(DPPHR)is the choice of surgery for benign or low-grade malignant tumors of the pancreatic head.Laparoscopic DPPHR(LDPPHR)procedure can be improved by preoperative 3D model reconstruction and the use of intravenous indocyanine green fluorescent before surgery for real-time navigation with fluorescent display to guide the surgical dissection and prevention of from injury to vessels and biliary tract.CASE SUMMARY Here we report the successful short-and long-term outcomes after one year following LDPPHR for a 60-year lady who had an uneventful recovery and was discharged home one week after the surgery.CONCLUSION There was no bile leakage or pancreatic leakage or delayed gastric emptying.The histopathology report showed multiple cysts in the pancreatic head and localized pancreatic intraepithelial tumor lesions.The resected margin was free of tumor.

A Medium/Long-Range Forecast of Pacific Subtropical High Based on Dynamic Statistic Model Reconstruction

Based on the 500-hPa geopotential height field series of T106 numerical forecast products, by empirical orthogonal function （EOF） time-space separation, and on the hypotheses of EOF space-models being stable, the EOF time coefficient series were taken as dynamical statistic model variables. The dynamic system reconstruction idea and genetic algorithm were introduced to make the dynamical model parameters optimized, and a nonlinear dynamic statistic model of EOF separating time coefficient series was established. By the model time integral and EOF time-space reconstruction, a medium/long-range forecast of subtropical high was carried out. The results show that the dynamical model forecast and T106 numerical forecast were approximately similar in the short-range forecast （≤5 days）, but in the medium/long-range forecast （≥5 days）, the forecast results of dynamical model was superior to that of T106 numerical products. A new method and idea were presented for diagnosing and forecasting complicated weathers such as subtropical high, and showed a better application outlook.

Dynamics of moisture regime and its reconstruction from a tree-ring width chronology of Pinus sylvestris in the downstream basin of the Selenga River, Russia

Regional tree-ring width chronology of the Scots pine (Pinus sylvestris L.) was constructed from 8 sites in the forest-steppe belt situated in the foothills of the Selenga River basin, Russia. Moisture information contained in tree-ring width chronology was obtained through linear regression reconstruction models of annual August–July precipitation and annual water discharge of the Selenga River during the period 1767–2015. Comparison of the smoothed series allowed estimating long-term variation component of these moisture regime parameters with a high precision. At the same time, regional drought indices are less correlated with pine radial growth, because they have contribution of the other environmental variables, which are much less reflected in the tree-ring of the investigated pine forest stands. Reconstructed dynamic of the moisture regime parameters is supported by documental evident of many socially significant events in the regional history, such as crop failures caused by both droughts and floods, and catastrophic fire in the Irkutsk City in 1879. Also, dependence of the amount of precipitation in the study area on the atmospheric circulation in Central Asia is revealed to have a similar pattern with other regions, i.e., a negative relationship of precipitation with the development of large high atmospheric pressure area within its center in the Altai and Tianshan mountains.

Curve interpolation model for visualising disjointed neural elements

Neuron cell are built from a myriad of axon and denddte structures. It transmits electrochemical signals between the brain and the nervous system. Three-dimensional visualization of neuron structure could help to facilitate deeper understanding of neuron and its models. An accurate neuron model could aid understanding of brain＇s functionalities, diagnosis and knowledge of entire nervous system. Existing neuron models have been found to be defective in the aspect of realism. Whereas in the actual biological neuron, there is continuous growth as the soma extending to the axon and the dendrite; but, the current neuron visualization models present it as disjointed segments that has greatly mediated effective realism. In this research, a new reconstruction model comprising of the Bounding Cylinder, Curve Interpolation and Gouraud Shading is proposed to visualize neuron model in order to improve realism. The reconstructed model is used to design algorithms for generating neuron branching from neuron SWC data. The Bounding Cylinder and Curve Interpolation methods are used to improve the connected segments of the neuron model using a series of cascaded cylinders along the neuron＇s connection path. Three control points are proposed between two adjacent neuron segments. Finally, the model is rendered with Gouraud Shading for smoothening of the model surface. This produce a near-perfection model of the natural neurons with attended realism. The model is validated by a group of bioinformatics analysts＇ responses to a predefined survey. The result shows about 82% acceptance and satisfaction rate.

RECONSTRUCTION OF LAYER DATA WITH DEFORMABLE B-SPLINES

A new B-spline surface reconstruction method from layer data based on deformable model is presented. An initial deformable surface, which is represented as a closed cylinder, is firstly given. The surface is subject to internal forces describing its implicit smoothness property and external forces attracting it toward the layer data points. And then finite element method is adopted to solve its energy minimization problem, which results a bicubic closed B-spline surface with C^2 continuity. The proposed method can provide a smoothness and accurate surface model directly from the layer data, without the need to fit cross-sectional curves and make them compatible. The feasibility of the proposed method is verified by the experimental results.

Automatic extraction and reconstruction of a 3D wireframe of an indoor scene from semantic point clouds

Accurate indoor 3D models are essential for building administration and applications in digital city construction and operation.Developing an automatic and accurate method to reconstruct an indoor model with semantics is a challenge in complex indoor environments.Our method focuses on the permanent structure based on a weak Manhattan world assumption,and we propose a pipeline to reconstruct indoor models.First,the proposed method extracts boundary primitives from semantic point clouds,such as floors,walls,ceilings,windows,and doors.The primitives of the building boundary,are aligned to generate the boundaries of the indoor scene,which contains the structure of the horizontal plane and height change in the vertical direction.Then,an optimization algorithm is applied to optimize the geometric relationships among all features based on their categories after the classification process.The heights of feature points are captured and optimized according to their neighborhoods.Finally,a 3D wireframe model of the indoor scene is reconstructed based on the 3D feature information.Experiments on three different datasets demonstrate that the proposed method can be used to effectively reconstruct 3D wireframe models of indoor scenes with high accuracy.

Isogeometric analysis based on geometric reconstruction models

In isogeometric analysis(IGA),the boundary representation of computer-aided design(CAD)and the tensor-product non-uniform rational B-spline structure make the analysis of three-dimensional(3D)problems with irregular geometries difficult.In this paper,an IGA method for complex models is presented by reconstructing analysis-suitable models.The CAD model is represented by boundary polygons or point cloud and is embedded into a regular background grid,and a model reconstruction method is proposed to obtain the level set function of the approximate model,which can be directly used in IGA.Three 3D examples are used to test the proposed method,and the results demonstrate that the proposed method can deal with complex engineering parts reconstructed by boundary polygons or point clouds.

DETECTING CEREBRAL ARTERIES AND VEINS:FROM LARGE TO SMALL

In this paper,a model-based reconstruction technique is proposed to simultaneously measure the relative deoxyhemoglobin concentration and the relative blood flow velocity in cerebral cortex.With the help of this model-based reconstruction technique,artifacts due to nonuniform laser illumination and curvature of cortex are efficiently corrected.The results of relative deoxyhemoglobin concentration and relative blood flow velocity are then used to detect and distinguish cerebral arteries and veins.In an experimental study on rat,cerebral blood vessels are segmented from the reconstructed blood flow image by Otsu multiple threshold method.Afterwards,arteries and veins are distinguished by a simple fuzzy criterion based on the information of relative deoxyhemoglobin concentration.

Radar Imaging Based on Iterative Algorithms

It has long been realized that the problem of radar imaging is a special case of image reconstruction in which the data are incomplete and noisy. In other fields, iterative reconstruction algorithms have been used successfully to improve the image quality. This paper studies the application of iterative algorithms in radar imaging. A discrete model is first derived, and the iterative algorithms are then adapted to radar imaging. Although such algorithms are usually time consuming, this paper shows that, if the algorithms are appropriately simplified, it is possible to realize them even in real time. The efficiency of iterative algorithms is shown through computer simulations.

Building reconstruction from airborne laser scanning data

The research on building model reconstruction has been a long-term hot topic in both the photogrammetry and computer vision areas.The airborne laser scanning technique provides new opportunities for building model reconstruction.Despite many investigations on building reconstruction using point clouds,there are still many unresolved problems that need further research,especially fully automatic methods and intelligent user-friendly operations.This article surveys the methods,tools and problems of building model reconstruction using point clouds data.The article also points out some important but unnoticed problems in building reconstruction according to our previous experience.We hope our comments article can be helpful for researchers in understanding their position and for new researcher in acquiring general information.

The Vérard et al.(2015) method for 3D palaeogeographic reconstructions:How solid is its base?

Verard and co-workers proposed in an earlier issue of this journal a method to reconstruct the 3D palaeogeography ＂anywhere in the world at any time＂. The present contribution is a discussion of some of the assumptions on which the method of Verard et al. is based. The reason for this discussion is that the method will give, at least seemingly, illogical outcomes for numerous situations. Moreover, some assumptions used by Verard and his team pose theoretical probtems. It is deduced that the method developed by Verard and co-workers may occasionally help, indeed, to obtain a rough picture of the altitude of the sedimentary surface on the continents and of the depth of the sedimentary surface in the oceans in the geological past. The outcomes should, however, be treated with utmost care as severat of the assumptions on which the interpretative 3D method is based have no solid basis, so that even the rough outcomes of the method must be considered questionable.