Accurate Reconstruction Method Research Articles

An accurate interface reconstruction method using piecewise circular arcs

SummaryA novel piecewise circular interface construction (PCIC) method for accurate reconstruction of interface in a two‐phase flow problem is proposed. This is under the framework of a fixed grid, volume of fluid approach applied on a two‐dimensional semistaggered structured grid. Fluid interface in each mixed cell is represented using a geometric template of piecewise circular arc. Data corresponding to arc center coordinates and radius are first predicted using curve fitting methods and corrected with the help of volume fraction constraints. Further corrections are carried out to achieve function (c0) continuity at cell boundaries. The proposed method does not require additional calculations for the determination of curvature (for calculation of surface tension force), since it is obtained as part of reconstruction process itself. For dynamic interface construction, simple analytical expressions are derived to construct edge matched flux polygons. Area of intersection of flux polygons with area covered by primary fluid is determined to effect geometric advection across a PCIC interface. Accuracy of this method is demonstrated by the reconstruction of standard static and dynamically evolving interface problems. Accuracy levels superior to most interface reconstruction methods using PLIC and schemes using higher order curves are established. Finally, the capability to handle a complex two‐phase flow problem simulation viz the four‐vortex flow field, where interface undergoes breakage and coalescence, is also demonstrated.

Efficient L1/2 Regularization-Based Reconstruction for Photoacoustic Imaging Using Adaptively Iterative Thresholding Algorithm

Sparse sampling photoacoustic imaging (PAI) is a significant research topic. Accurate and efficient reconstruction methods play important roles in the wide application of PAI in preclinical research. Compressed sensing has large potential in efficiently reconstructing high quality PAI images with sparse sampling signal. We presented our study on a L1/2 regularization operator based adaptive iterative thresholding method for sparse view PAI in this article, which can use few measurements to exactly reconstruct the PAI image. The effectiveness of the proposed algorithm was verified by simulation analysis using Matlab. And the proposed algorithm was compared with two state-of-the-art L1 norm and TV norm based algorithms for signal recovery and image reconstruction. The SNR of the reconstructed image calculated by the introduced method was better than the other two methods tested in this research. The algorithm presented in this paper not only provides higher quality image with sparse view data, but also is robust to noise and over estimation of sparsity value.

Fast reconstruction of atomic-scale STEM-EELS images from sparse sampling

This paper discusses the reconstruction of partially sampled spectrum-images to accelerate the acquisition in scanning transmission electron microscopy (STEM). The problem of image reconstruction has been widely considered in the literature for many imaging modalities, but only a few attempts handled 3D data such as spectral images acquired by STEM electron energy loss spectroscopy (EELS). Besides, among the methods proposed in the microscopy literature, some are fast but inaccurate while others provide accurate reconstruction but at the price of a high computation burden. Thus none of the proposed reconstruction methods fulfills our expectations in terms of accuracy and computation complexity. In this paper, we propose a fast and accurate reconstruction method suited for atomic-scale EELS. This method is compared to popular solutions such as beta process factor analysis (BPFA) which is used for the first time on STEM-EELS images. Experiments based on real as synthetic data will be conducted.

Moment-of-fluid analytic reconstruction on 3D rectangular hexahedrons

The moment-of-fluid method (MOF) is a second-order accurate interface reconstruction method which can be seen as an extension of the volume-of-fluid method with piecewise linear interface construction (VOF-PLIC). MOF involves a computationally intensive minimization problem that needs to be solved on every cell containing several materials. We propose a new fast and robust reconstruction algorithm to tackle this problem on rectangular hexahedral cells. Our approach uses explicit analytic formulas of the objective function that does not use any geometric computations such as half-space–polyhedron intersections. The numerical results show that the proposed method is more robust and more than 200 times faster than the original approach. Additionally, we propose a faster reconstruction algorithm on convex polyhedral cells. All the methods presented in this article have been implemented and verified on the open-source code Notus.

A Reconstruction and Contact Analysis Method of Three-Dimensional Rough Surface Based on Ellipsoidal Asperity

Abstract The 3D rough surface modeling and contact analysis is a difficult problem in the study of rough surface contact. In this paper, a new method for reconstruction and contact analysis of asperities on 3D rough surfaces is proposed based on real rough surfaces. Watershed algorithm is used to segment and determine the area of asperities on the rough surface. According to the principle of minimum mean square error, ellipsoid fitting is carried out on asperities. Based on the elastic-plastic contact model of a single ellipsoidal asperity, a stable and efficient method for 3D rough surface contact analysis and calculation is proposed. Compared with existing calculating methods, the present method has the following characteristics: (1) the constructed surface asperity is closer to the real asperity in contact, and the calculation of asperity parameters has better stability under different sampling intervals and (2) the contact pressure, contact area, and other contact parameters of the 3D rough surface are calculated with high accuracy and efficiency, and the calculation convergence is desirable. The reconstruction and contact analysis method of the 3D rough surface asperity proposed in this paper provides a more accurate reconstruction and calculation method for the study of contact fatigue life and wear failure of rough surfaces.

Quantitative susceptibility map reconstruction using annihilating filter-based low-rank Hankel matrix approach.

Quantitative susceptibility mapping (QSM) inevitably suffers from streaking artifacts caused by zeros on the conical surface of the dipole kernel in k-space. This work proposes a novel and accurate QSM reconstruction method based on k-space low-rank Hankel matrix constraint, avoiding the over-smoothing problem and streaking artifacts. Based on the recent theory of annihilating filter-based low-rank Hankel matrix approach (ALOHA), QSM is formulated as deconvolution under low-rank Hankel matrix constraint in the k-space. The computational complexity and the high memory burden were reduced by successive reconstruction of 2-D planes along 3 independent axes of the 3-D phase image in Fourier domain. Feasibility of the proposed method was tested on a simulated phantom and human data and were compared with existing QSM reconstruction methods. The proposed ALOHA-QSM effectively reduced streaking artifacts and accurately estimated susceptibility values in deep gray matter structures, compared to the existing QSM methods. The suggested ALOHA-QSM algorithm successfully solves the 3-dimensional QSM dipole inversion problem using k-space low rank property with no anatomical constraint. ALOHA-QSM can provide detailed brain structures and accurate susceptibility values with no streaking artifacts.

Universal phase reconstruction approach of self-calibrating phase-shifting interferometry.

Self-calibrating phase-shifting interferometry (PSI) reconstructs the phase map from three-frame or more phase-shifting interferograms without the need for knowing accurate phase steps. The existing phase reconstruction methods for self-calibrating PSI still have many constraints in terms of the required number of interferograms, special usage preconditions, etc. In this Letter, a universal, accurate, and efficient phase reconstruction method for self-calibrating PSI is proposed. In this approach, we search the solution space of phase shifts to obtain the modulation amplitude of interferograms with the minimum coefficient of variation (CV). Then the phase is reconstructed through the searched phase shifts. Numerical and experimental studies demonstrate that this method can realize highly accurate phase reconstruction consistently, compared to the currently popular methods in their own usable ranges. We anticipate that this Letter may provide a universal and powerful solution for the phase reconstruction of self-calibrating PSI.

Self‐adapting multi‐peak water‐fat reconstruction for the removal of lipid artifacts in chemical exchange saturation transfer (CEST) imaging

Artifacts caused by strong lipid signals pose challenges in body chemical exchange saturation transfer (CEST) imaging. This study aimed to develop an accurate water-fat reconstruction method based on the multi-echo Dixon technique to remove lipid artifacts in CEST imaging. It is well known that fat has multiple spectral peaks. Furthermore, RF pulses in CEST preparation saturate each fat peak at different levels, complicating fat modeling. Therefore, a self-adapting multi-peak model (SMPM) is proposed to update relative amplitudes of fat peaks using numerical calculation. With the SMPM-based updating, nonlinear least-squares fitting combined with IDEAL (Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation) algorithms was used for water-fat reconstruction and B0 mapping. The proposed method was compared with the reported 3-point Dixon method and the fixed multi-peak model in a phantom study using a fat-free Z-spectrum obtained from MR spectroscopy acquisition as the ground truth. This method was also validated by in vivo experiments on human breast. In the phantom experiments, the Z-spectrum from the SMPM-based method agreed well with the fat-free Z-spectrum from CEST-PRESS (point-resolved spectroscopy), validating the effective removal of lipid artifacts, while a decrease or a rise that appeared at -3.5 ppm was observed in the Z-spectrum from the 3-point method and the FMPM-based method, respectively. In the in vivo experiments, no lipid artifacts were observed in the Z-spectrum or the amide CEST map from the SMPM-based method in the fibro-glandular region of the breast with high fat fractions. The SMPM-based method successfully removes lipid artifacts and significantly improves the accuracy of CEST contrast.

Monitoring Marine Habitats With Photogrammetry: A Cost-Effective, Accurate, Precise and High-Resolution Reconstruction Method

Underwater photogrammetry has been increasingly used to study and monitor the three-dimensional characteristics of marine habitats, despite a lack of knowledge on the quality and reliability of the reconstructions. More particularly, little attention has been paid to exploring and estimating the relative contribution of multiple acquisition parameters on the model resolution (distance between neighbor vertices), accuracy (closeness to true positions/measures) and precision (variability of positions/measures). On the other hand, some studies used expensive or cumbersome camera systems that can restrict the number of users of this technology for the monitoring of marine habitats. This study aimed at developing a simple and cost-effective protocol able to produce accurate and reproducible high-resolution models. Precisely, the effect of the camera system, flying elevation, camera orientation and number of images on the resolution and accuracy of marine habitat reconstructions was tested through two experiments. A first experiment allowed for testing all combinations of acquisition parameters through the building of 192 models of the same 36 m(2) study site. The flying elevation and camera system strongly affected the model resolution, while the photo density mostly affected bundle adjustment accuracy and total processing time. The camera orientation, in turn, mostly affected the reprojection error. The best combination of parameters was used in a second experiment to assess the accuracy and precision of the resulting reconstructions. The average model resolution was 3.4 mm, and despite a decreasing precision in the positioning of markers with distance to the model center (0.33, 0.27, and 1.2 mm/m Standard Deviation (SD) in X, Y, Z, respectively), the measures were very accurate and precise: 0.08% error +/- 0.06 SD for bar lengths, 0.36% +/- 0.51 SD for a rock model area and 0.92% +/- 0.54 SD for its volume. The 3D geometry of the rock only differed by 1.2 mm +/- 0.8 SD from the ultra-high resolution in-air reference. These results suggest that this simple and cost-effective protocol produces accurate and reproducible models that are suitable for the study and monitoring of marine habitats at a small reef scale.

Two-dimensional local Fourier image reconstruction via domain decomposition Fourier continuation method.

The MRI image is obtained in the spatial domain from the given Fourier coefficients in the frequency domain. It is costly to obtain the high resolution image because it requires higher frequency Fourier data while the lower frequency Fourier data is less costly and effective if the image is smooth. However, the Gibbs ringing, if existent, prevails with the lower frequency Fourier data. We propose an efficient and accurate local reconstruction method with the lower frequency Fourier data that yields sharp image profile near the local edge. The proposed method utilizes only the small number of image data in the local area. Thus the method is efficient. Furthermore the method is accurate because it minimizes the global effects on the reconstruction near the weak edges shown in many other global methods for which all the image data is used for the reconstruction. To utilize the Fourier method locally based on the local non-periodic data, the proposed method is based on the Fourier continuation method. This work is an extension of our previous 1D Fourier domain decomposition method to 2D Fourier data. The proposed method first divides the MRI image in the spatial domain into many subdomains and applies the Fourier continuation method for the smooth periodic extension of the subdomain of interest. Then the proposed method reconstructs the local image based on L2 minimization regularized by the L1 norm of edge sparsity to sharpen the image near edges. Our numerical results suggest that the proposed method should be utilized in dimension-by-dimension manner instead of in a global manner for both the quality of the reconstruction and computational efficiency. The numerical results show that the proposed method is effective when the local reconstruction is sought and that the solution is free of Gibbs oscillations.

Reconstruction Techniques in IceCube using Convolutional and Generative Neural Networks

Reliable and accurate reconstruction methods are vital to the success of high-energy physics experiments such as IceCube. Machine learning based techniques, in particular deep neural networks, can provide a viable alternative to maximum-likelihood methods. However, most common neural network architectures were developed for other domains such as image recogntion. While these methods can enhance the reconstruction performance in IceCube, there is much potential for tailored techniques. In the typical physics use-case, many symmetries, invariances and prior knowledge exist in the data, which are not fully exploited by current network architectures. Novel and specialized deep learning based reconstruction techniques are desired which can leverage the physics potential of experiments like IceCube. A reconstruction method using convolutional neural networks is presented which can significantly increase the reconstruction accuracy while greatly reducing the runtime in comparison to standard reconstruction methods in Ice- Cube. In addition, first results are discussed for future developments based on generative neural networks.

Nonlinear wavefront reconstruction methods for pyramid sensors using Landweber and Landweber-Kaczmarz iterations.

Accurate and robust wavefront reconstruction methods for pyramid wavefront sensors are in high demand, as these sensors are planned to be part of many instruments currently under development for ground-based telescopes. The pyramid sensor relates the incoming wavefront and its measurements in a nonlinear way. Nevertheless, almost all existing reconstruction algorithms are based on a linearization of the model. The assumption of a linear pyramid sensor response is justifiable in closed-loop adaptive optics (AO) when the measured phase information is small, but, depending on the system, may not be feasible due to unpreventable errors such as non-common path aberrations. In order to solve the nonlinear inverse problem of wavefront reconstruction from pyramid sensor data, we introduce two new methods based on the nonlinear Landweber and Landweber-Kaczmarz iterations. Using these algorithms, we experience high-quality wavefront estimation, especially for the non-modulated sensor, by still keeping the numerical effort feasible for large-scale AO systems.

3D Reconstruction using artificial bee colony based iterative closest point algorithm

3D Reconstruction has been an enduring problem in Image understanding and computer vision. There is an increasing interest on 3D information in the general public due to rapid development of 3D imaging techniques, marketing of 3D movies and games, and low cost of depth cameras. Numerous algorithms that have been proposed for performing 3D reconstruction using different variants of Iterative Closest Point(ICP) algorithm focusses mainly on reducing the computation time. The accuracy of 3D reconstruction is not taken in to consideration. An efficient, accurate, real time and active 3D reconstruction method using Kinect sensor is developed in this paper focusing on improving the accuracy of 3D reconstruction in less computation time. An Artificial Bee colony based ICP algorithm is proposed by incorporating several efficient variants of ICP algorithm. The proposed algorithm is intended to improve the accuracy and stability of the standard ICP algorithm. The performance of the proposed algorithm is satisfactory when compared with structured light technique and several ICP variants with respect to accuracy, complexity and computation speed.

Three-Dimensional Reconstruction of Foot in the Weightbearing Position From Biplanar Radiographs: Evaluation of Accuracy and Reliability

The initial assessment and postoperative monitoring of patients with various abnormalities of the foot in clinical routine practice is primarily based on the analysis of radiographs taken in the weightbearing position. Conventional x-ray imaging, however, only provides a 2-dimensional projection of 3-dimensional (3D) bony structures, and the clinical parameters assessed from these images can be affected by projection biases. In the present work, we addressed this issue by proposing an accurate 3D reconstruction method of the foot in the weightbearing position from low-dose biplanar radiographs with clinical index measurement assessment for clinical routine practice. The accuracy of the proposed reconstruction method was evaluated for both shape and clinical indexes by comparing 3D reconstructions of 6 cadaveric adult feet from computed tomographic images and from biplanar radiographs. For the reproducibility study, 3D reconstructions from the biplanar radiographs of the foot of 6 able-bodied subjects were considered, with 2 observers repeating each measurement of anatomic landmarks 3 times. Baseline assessment of important 3D clinical parameters was performed on 17 subjects (34 feet; mean age 27.7, range 20 to 52 years). The average point to surface distance between the 3D stereoradiographic reconstruction and the computed tomographic scan-based reconstruction was 1 mm (range 0mm to 6mm). The selected radiographic landmarks were highly reproducible (95% confidence interval <2.0 mm). The greatest interindividual variability for the clinical parameters was observed for the twisting angle (mean 87°, range 73° to 100°). Such an approach opens the way for routine 3D quantitative analysis of the foot in the weightbearing position.

Fast and accurate wavefront reconstruction in two-frame phase-shifting interferometry with unknown phase step.

A fast and accurate wavefront reconstruction method for two-frame phase-shifting interferometry is proposed. The unknown phase step between the two interferograms is estimated directly by solving a quartic polynomial equation, and then the phase map is readily reconstructed after obtaining the phase step. The whole phase reconstruction process is nearly analytical and thus very fast and easy to realize. Good performance of the proposed method is demonstrated by reconstructing the phase maps from simulated and real fringes along with comparisons to several existing well-established algorithms.

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study.

Background: Phylogenetic reconstruction is a necessary first step in many analyses which use whole genome sequence data from bacterial populations. There are many available methods to infer phylogenies, and these have various advantages and disadvantages, but few unbiased comparisons of the range of approaches have been made. Methods: We simulated data from a defined "true tree" using a realistic evolutionary model. We built phylogenies from this data using a range of methods, and compared reconstructed trees to the true tree using two measures, noting the computational time needed for different phylogenetic reconstructions. We also used real data from Streptococcus pneumoniae alignments to compare individual core gene trees to a core genome tree. Results: We found that, as expected, maximum likelihood trees from good quality alignments were the most accurate, but also the most computationally intensive. Using less accurate phylogenetic reconstruction methods, we were able to obtain results of comparable accuracy; we found that approximate results can rapidly be obtained using genetic distance based methods. In real data we found that highly conserved core genes, such as those involved in translation, gave an inaccurate tree topology, whereas genes involved in recombination events gave inaccurate branch lengths. We also show a tree-of-trees, relating the results of different phylogenetic reconstructions to each other. Conclusions: We recommend three approaches, depending on requirements for accuracy and computational time. Quicker approaches that do not perform full maximum likelihood optimisation may be useful for many analyses requiring a phylogeny, as generating a high quality input alignment is likely to be the major limiting factor of accurate tree topology. We have publicly released our simulated data and code to enable further comparisons.

Local Flow Patterns After Implantation of Bioresorbable Vascular Scaffold in Coronary Bifurcations - Novel Findings by Computational Fluid Dynamics.

Development of methods for accurate reconstruction of bioresorbable scaffolds (BRS) and assessing local hemodynamics is crucial for investigation of vascular healing after BRS implantation.Methods and Results:Patients with BRS that crossed over in a coronary bifurcation were included for analysis. Reconstructions of the coronary lumen and BRS were performed by fusion of optical coherence tomography and coronary angiography generating a tree model (TM) and a hybrid model with BRS (TM-BRS). A virtual BRS model with thinner struts was created and all 3 models were analyzed using computational fluid dynamics to derive: (1) time-average shear stress (TASS), (2) TASS gradient (TASSG), which represents SS heterogeneity, and (3) fractional flow reserve (FFR). Reconstruction of the BRS was successful in all 10 patients. TASS and TASSG were both higher by TM-BRS than by TM in main vessels (difference 0.27±4.30 Pa and 10.18±27.28 Pa/mm, P<0.001), with a remarkable difference at side branch ostia (difference 13.51±17.40 Pa and 81.65±105.19 Pa/mm, P<0.001). With thinner struts, TASS was lower on the strut surface but higher at the inter-strut zones, whereas TASSG was lower in both regions (P<0.001 for all). Computational FFR was lower by TM-BRS than by TM for both main vessels and side branches (P<0.001). Neglecting BRS reconstruction leads to significantly lower SS and SS heterogeneity, which is most pronounced at side branch ostia. Thinner struts can marginally reduce SS heterogeneity.

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study

Background: Phylogenetic reconstruction is a necessary first step in many analyses which use whole genome sequence data from bacterial populations. There are many available methods to infer phylogenies, and these have various advantages and disadvantages, but few unbiased comparisons of the range of approaches have been made. Methods: We simulated data from a defined 'true tree' using a realistic evolutionary model. We built phylogenies from this data using a range of methods, and compared reconstructed trees to the true tree using two measures, noting the computational time needed for different phylogenetic reconstructions. We also used real data from Streptococcus pneumoniae alignments to compare individual core gene trees to a core genome tree. Results: We found that, as expected, maximum likelihood trees from good quality alignments were the most accurate, but also the most computationally intensive. Using less accurate phylogenetic reconstruction methods, we were able to obtain results of comparable accuracy; we found that approximate results can rapidly be obtained using genetic distance based methods. In real data we found that highly conserved core genes, such as those involved in translation, gave an inaccurate tree topology, whereas genes involved in recombination events gave inaccurate branch lengths. We also show a tree-of-trees, relating the results of different phylogenetic reconstructions to each other. Conclusions: We recommend three approaches, depending on requirements for accuracy and computational time. For the most accurate tree, use of either RAxML or IQ-TREE with an alignment of variable sites produced by mapping to a reference genome is best. Quicker approaches that do not perform full maximum likelihood optimisation may be useful for many analyses requiring a phylogeny, as generating a high quality input alignment is likely to be the major limiting factor of accurate tree topology. We have publicly released our simulated data and code to enable further comparisons.

Volumetric 3D reconstruction of real objects using voxel mapping approach in a multiple-camera environment

Extracting 3D information from 2D images is an inverse estimation problem and a challenging task in itself. The aim of 2D to 3D reconstruction is to generate either a volume or a surface representing the object from multiple views. This paper presents a simple and accurate multiple-view volumetric 3D reconstruction method using an integrated approach based on homography estimation and voxel mapping. The homography-based approaches give accurate estimates but do not provide system dynamics. The voxel-based volumetric reconstruction methods provide system dynamics that are essential for system modeling. However, they face challenges while modeling the concavities. This paper presents a proposed 3D reconstruction method that combines homography estimation and the voxel mapping approach for improving the accuracy of 3D reconstruction. Experimental results show that the method efficiently reconstructs objects of known and unknown shape, fragile objects, and complex scenes with multiple objects. The use of homography along with voxel mapping in a multiple-camera environment brings out more details of the object for improving the quality of reconstruction.

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study

Background: Phylogenetic reconstruction is a necessary first step in many analyses which use whole genome sequence data from bacterial populations. There are many available methods to infer phylogenies, and these have various advantages and disadvantages, but few unbiased comparisons of the range of approaches have been made. Methods: We simulated data from a defined “true tree” using a realistic evolutionary model. We built phylogenies from this data using a range of methods, and compared reconstructed trees to the true tree using two measures, noting the computational time needed for different phylogenetic reconstructions. We also used real data from Streptococcus pneumoniae alignments to compare individual core gene trees to a core genome tree. Results: We found that, as expected, maximum likelihood trees from good quality alignments were the most accurate, but also the most computationally intensive. Using less accurate phylogenetic reconstruction methods, we were able to obtain results of comparable accuracy; we found that approximate results can rapidly be obtained using genetic distance based methods. In real data we found that highly conserved core genes, such as those involved in translation, gave an inaccurate tree topology, whereas genes involved in recombination events gave inaccurate branch lengths. We also show a tree-of-trees, relating the results of different phylogenetic reconstructions to each other. Conclusions: We recommend three approaches, depending on requirements for accuracy and computational time. Quicker approaches that do not perform full maximum likelihood optimisation may be useful for many analyses requiring a phylogeny, as generating a high quality input alignment is likely to be the major limiting factor of accurate tree topology. We have publicly released our simulated data and code to enable further comparisons.