Joint estimation of image and coil sensitivities in parallel MRI
Parallel magnetic resonance imaging (MRI) using multichannel receiver coils has emerged as an effective tool to reduce imaging time in various dynamic imaging applications. However, there are still a number of image reconstruction issues that have not been fully addressed, thereby limiting the level of speed enhancement achievable with the technology. This paper considers the inaccuracy of coil sensitivities in conventional reconstruction methods such as SENSE, and reformulates the image reconstruction problem as a joint estimation of the coil sensitivities and the desired image, which is solved by an iterative algorithm. Experimental results demonstrate the effectiveness of the proposed method especially when large acceleration factors are used

title: REGULARIZED SENSE RECONSTRUCTION USING ITERATIVELY REFINED TOTAL VARIATION METHOD
abstract: SENSE has been widely accepted as one of the standard reconstruction algorithms for parallel MRI. When large acceleration factors are employed, the SENSE reconstruction becomes very ill-conditioned. For Cartesian SENSE, Tikhonov regularization has been commonly used. However, the Tikhonov regularized image usually tends to be overly smooth, and a high-quality regularization image is desirable to alleviate this problem but is not available. In this paper, we propose a new SENSE regularization technique that is based on total variation with iterated refinement using Bregman iteration. It penalizes highly oscillatory noise but allows sharp edges in reconstruction without the need for prior information. In addition, the Bregman iteration refines the image details iteratively. The method is shown to be able to significantly reduce the artifacts in SENSE reconstruction

title: An Efficient and Accurate Method for 3D-Point Reconstruction from Multiple Views
abstract: In this paper we consider the problem of finding the position of a point in space given its projections in multiple images taken by cameras with known calibration and pose. Ideally the 3D point can be obtained as the intersection of multiple known rays in space. However, with noise the rays do not meet at a single point generally. Therefore, it is necessary to find a best point of intersection. In this paper we propose a modification of the method (Ma et al., 2001. Journal of Communications in Information and Systems, (1):51–73) based on the multiple-view epipolar constraints. The solution is simple in concept and straightforward to implement. It includes generally two steps: first, image points are corrected through approximating the error model to the first order, and then the 3D point can be reconstructed from the corrected image points using any generic triangulation method. Experiments are conducted both on simulated data and on real data to test the proposed method against previous methods. It is shown that results obtained with the proposed method are consistently more accurate than those of other linear methods. When the measurement error of image points is relatively small, its results are comparable to those of maximum likelihood estimation using Newton-type optimizers; and when processing image-point correspondences cross a small number of views, the proposed method is by far more efficient than the Newton-type optimizers.

title: Mesh Editing in ROI with Dual Laplacian

title: Detecting patterns of change using enhanced parallel coordinates visualization
abstract: Analyzing data to find trends, correlations, and stable patterns is an important problem for many industrial applications. We propose a new technique based on parallel coordinates visualization. Previous work on parallel coordinates method has shown that they are effective only when variables that are correlated and/or show similar patterns are displayed adjacently. Although current parallel coordinates tools allow the user to manually rearrange the order of variables, this process is very time-consuming when the number of variables is large. Automated assistance is needed. We propose an edit-distance based technique to rearrange variables so that interesting patterns can be easily detected. Our system, V-Miner, includes both automated methods for visualizing common patterns and a query tool that enables the user to describe specific target patterns to be mined/displayed by the system. Following an overview of the system, a case study is presented to explain how Motorola engineers have used V-Miner to identify significant patterns in their product test and design data.

title: A Grid-Based System for the Multi-reservoir Optimal Scheduling in Huaihe River Basin
abstract: The up- and mid-stream of Huaihe River Basin is a complex system of reservoirs and river-ways. It is difficult for flood control and reservoir scheduling. It is ineffective to perform sequential computations for optimal scheduling of multi-reservoir due to the system complexity. In this paper, we implemented the multi-reservoir optimal scheduling algorithm in a Grid environment. Key components as multiple Protocols were developed within the layers of Grid architecture. The proposed Grid computing architecture provides an innovative design of multi-reservoir optimal scheduling system for increasing the accuracy of flood control and speedup of computing.

title: An Energy-Minimizing Mesh Parameterization
abstract: In this paper, we propose a new energy-minimizing mesh parameterization method, which linearly combines two new energies EQ and EM. It not only avoids triangles overlap in the parameter domain, but also is invariant under rotation, translation and scale transformations. We first parameterize the original 3D mesh to the parameter plane by using the energy-minimizing parameterization, and get the optimal effect by optimizing the weights wij gradually. Experimental results indicate that this optimized energy-minimizing method has low distortion and good stability.