Search Results: 1 - 10 of 100 matches for " "
All listed articles are free for downloading (OA Articles)
Page 1 /100
Display every page Item
A survey of freehand 3D ultrasound reconstruction algorithms
Freehand 3维超声重建算法综述


中国图象图形学报 , 2010,
Abstract: The research of Freehand 3D ultrasound has been playing an increasingly important role in the 3D reconstruction techniques of ultrasound images in recent decades. 3D ultrasound is classified firstly according to different taking manners. Then the characteristic of Freehand 3D ultrasound system and the principle of 3D reconstruction for Freehand ultrasound images are illuminated. Finally, the overview and comparison analysis of Freehand 3D ultrasound reconstruction algorithms are provided. Synchronously some challenges and research orientations are also indicated.
Surface Reconstruction Based on Scattered Point Sets

WANG Shu-zhong ZHANG You-sheng,

计算机科学 , 2009,
Abstract: Mesh surface reconstruction based on scattered point sets is the hotspot of research in the fields of computer graphics and virtual reality and so on.Some of the classic surface reconstruction algorithms were reviewed and their drawbacks were analyzed first.And then the reconstruction algorithm based on Growing Cell Structure and the reconstructions algorithm based on normal vector field were discussed in detail,which were proposed in resent years.
Fusion of Sparse Reconstruction Algorithms for Multiple Measurement Vectors  [PDF]
Deepa K. G.,Sooraj K. Ambat,K. V. S. Hari
Statistics , 2015,
Abstract: We consider the recovery of sparse signals that share a common support from multiple measurement vectors. The performance of several algorithms developed for this task depends on parameters like dimension of the sparse signal, dimension of measurement vector, sparsity level, measurement noise. We propose a fusion framework, where several multiple measurement vector reconstruction algorithms participate and the final signal estimate is obtained by combining the signal estimates of the participating algorithms. We present the conditions for achieving a better reconstruction performance than the participating algorithms. Numerical simulations demonstrate that the proposed fusion algorithm often performs better than the participating algorithms.
Rio G. L. D'Souza,K. Chandra Sekaran,A. Kandasamy
International Journal of Artificial Intelligence & Applications , 2010,
Abstract: The reconstruction of gene networks has become an important activity in Systems Biology. The potentialfor better methods of drug discovery and disease diagnosis hinges upon our understanding of theinteraction networks between the genes. Evolutionary methods are proving to be successful in suchproblems and a number of such methods have been proposed. However, all these methods are based onprocessing of genotypic information. We present evolutionary algorithms for reconstructing genenetworks from expression data using phenotypic interactions, thereby avoiding the need for an explicitobjective function. Specifically, we implement the Phenomic algorithm and validate it for thereconstruction of gene networks. We also extend the basic phenomic algorithm to perform multiobjectiveoptimization for gene network reconstruction. We apply both these algorithms to the yeast sporulationdataset and show that the algorithms can effectively identify gene networks. Both the algorithms arevalidated for stability and accuracy in the reconstruction of gene networks.
Comparison of reconstruction algorithms for digital breast tomosynthesis  [PDF]
I. Reiser,J. Bian,R. M. Nishikawa,E. Y. Sidky,X. Pan
Physics , 2009,
Abstract: Digital breast tomosynthesis (DBT) is an emerging modality for breast imaging. A typical tomosynthesis image is reconstructed from projection data acquired at a limited number of views over a limited angular range. In general, the quantitative accuracy of the image can be significantly compromised by severe artifacts and non-isotropic resolution resulting from the incomplete data. Nevertheless, it has been demonstrated that DBT may yield useful information for detection/classification tasks and thus is considered a promising breast imaging modality currently undergoing pre-clinical evaluation trials. The purpose of this work is to conduct a preliminary, but systematic, investigation and evaluation of the properties of reconstruction algorithms that have been proposed for DBT. We use a breast phantom designed for DBT evaluation to generate analytic projection data for a typical DBT configuration, which is currently undergoing pre-clinical evaluation. The reconstruction algorithms under comparison include (i) filtered backprojection (FBP), (ii) expectation maximization (EM), and (iii) TV-minimization algorithms. Results of our studies indicate that FBP reconstructed images are generally noisier and demonstrate lower in-depth resolution than those obtained through iterative reconstruction and that the TV-minimization reconstruction yield images with reduced artifacts as compared to that obtained with other algorithms under study.
EIT Reconstruction Algorithms: Pitfalls, Challenges and Recent Developments  [PDF]
William R. B. Lionheart
Physics , 2003, DOI: 10.1088/0967-3334/25/1/021
Abstract: We review developments, issues and challenges in Electrical Impedance Tomography (EIT), for the 4th Workshop on Biomedical Applications of EIT, Manchester 2003. We focus on the necessity for three dimensional data collection and reconstruction, efficient solution of the forward problem and present and future reconstruction algorithms. We also suggest common pitfalls or ``inverse crimes'' to avoid.
Regularized Reconstruction of a Surface from its Measured Gradient Field  [PDF]
Matthew Harker,Paul O'Leary
Mathematics , 2013,
Abstract: This paper presents several new algorithms for the regularized reconstruction of a surface from its measured gradient field. By taking a matrix-algebraic approach, we establish general framework for the regularized reconstruction problem based on the Sylvester Matrix Equation. Specifically, Spectral Regularization via Generalized Fourier Series (e.g., Discrete Cosine Functions, Gram Polynomials, Haar Functions, etc.), Tikhonov Regularization, Constrained Regularization by imposing boundary conditions, and regularization via Weighted Least Squares can all be solved expediently in the context of the Sylvester Equation framework. State-of-the-art solutions to this problem are based on sparse matrix methods, which are no better than $\mathcal{O}!(n^6)$ algorithms for an $m\times n$ surface. In contrast, the newly proposed methods are based on the global least squares cost function and are all $\mathcal{O}!(n^3)$ algorithms. In fact, the new algorithms have the same computational complexity as an SVD of the same size. The new algorithms are several orders of magnitude faster than the state-of-the-art; we therefore present, for the first time, Monte-Carlo simulations demonstrating the statistical behaviour of the algorithms when subject to various forms of noise. We establish methods that yield the lower bound of their respective cost functions, and therefore represent the "Gold-Standard" benchmark solutions for the various forms of noise. The new methods are the first algorithms for regularized reconstruction on the order of megapixels, which is essential to methods such as Photometric Stereo.
A comparative study of interface reconstruction algorithms in molten metal flow
Young-Sim Choi,Jun-Ho Hong,Ho-Young Hwang
China Foundry , 2013,
Abstract: In the present research, two numerical schemes for improving the accuracy of the solution in the flow simulation of molten metal were applied. One method is the Piecewise Linear Interface Calculation (PLIC) method and the other is the Donor-Acceptor (D-A) method. To verify the module of the interface reconstruction algorithms, simple problems were tested. After these validations, the accuracy and efficiency of these two methods were compared by simulating various real products. On the numerical simulation of free surface flow, it is possible for the PLIC method to track very accurately the interface between phases. The PLIC method, however, has the weak point in that a lot of computational time is required, though it shows the more accurate interface reconstruction. The Donor-Acceptor method has enough effectiveness in the macro-observation of a mold filling sequence though it shows inferior accuracy. Therefore, for the problems that need the accurate solution, PLIC is more appropriate than D-A. More accuracy may cause less efficiency in numerical analysis. Which method between D-A method and PLIC method should be chosen depends on the product.
Comparison of Image Reconstruction Algorithms in EIT Imaging  [PDF]
Benjamin Schullcke, Sabine Krueger Ziolek, Bo Gong, Ullrich Mueller-Lisse, Knut Moeller
Journal of Biomedical Science and Engineering (JBiSE) , 2016, DOI: 10.4236/jbise.2016.910B018
Electrical Impedance Tomography (EIT) is a medical imaging technique which can be used to monitor the regional ventilation in patients utilizing voltage measurements made at the thorax. Several reconstruction algorithms have been developed during the last few years. In this manuscript we compare a well-established algorithm and a re-cently developed method for image reconstruction regarding EIT indices derived from the differently reconstructed images.
New vertex reconstruction algorithms for CMS  [PDF]
R. Fruehwirth,W. Waltenberger,K. Prokofiev,T. Speer,P. Vanlaer,E. Chabanat,N. Estre
Physics , 2003,
Abstract: The reconstruction of interaction vertices can be decomposed into a pattern recognition problem (``vertex finding'') and a statistical problem (``vertex fitting''). We briefly review classical methods. We introduce novel approaches and motivate them in the framework of high-luminosity experiments like at the LHC. We then show comparisons with the classical methods in relevant physics channels
Page 1 /100
Display every page Item

Copyright © 2008-2017 Open Access Library. All rights reserved.