The usefulness of diffusion‐weighted readout‐segmented EPI and fast spin echo with BLADE (PROPELLER) k‐space sampling: A comparison with single‐shot EPI for diffusion‐weighted imaging in ischemic stroke patients

We evaluated the value of diffusion‐weighted readout‐segmented EPI (DW rs‐EPI) and diffusion‐weighted fast spin echo images with BLADE (PROPELLER) k‐space sampling (DW BLADE) in patients with ischemic stroke through intra‐individual comparisons with diffusion‐weighted single‐shot EPI (DW ss‐EPI). Forty‐four patients with acute ischemic stroke who had undergone three different types of diffusion weighted imaging (DWI) (b = 1000 s/mm²) were included. Two reviewers assessed the three types of DWI for diagnostic confidence based on a five‐point confidence score (CS). The inter‐ and intra‐observer agreements for the CS were assessed. The DWI signal ratio to the contralateral normal area and the apparent diffusion coefficient (ADC) of DWI lesions were compared. The CSs of the three DWI methods were significantly different (P < 0.001). A post hoc analysis showed a significantly higher CS with DW rs‐EPI than with DW ss‐EPI (P = 0.022). There were significant increases in the CSs for DW rs‐EPI compared to DW ss‐EPI, for patients who underwent DWI within 24 h of symptom onset, and for patients with DWI lesions ≤ 50 mm². The inter‐observer and intra‐observer agreements of the CS were good. DW rs‐EPI increased the diagnostic confidence of ischemic stroke compared to DW ss‐EPI, particularly for patients with small lesions and for those who underwent DWI within 24 h of symptom onset. DW BLADE showed a similar level of diagnostic confidence to DW ss‐EPI. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 216–224, 2016     

Fractional anisotropy‐weighted front evolution algorithm for white matter tractography based on diffusion tensor imaging data

Tractography is one of the most important applications of diffusion tensor imaging (DTI) which noninvasively reconstructs 3D trajectories of the white matter tracts. Because of the intravoxel orientation heterogeneity of DTI data, some of tractography algorithms are unable to follow the correct pathways after the crossing and branching regions. Front propagation techniques are efficient methods in tracking the crossing fibers. A key parameter influencing the performance of these algorithms is the cost function which is mainly based on the colinearity of tensors' eigenvectors. The effect of the eigenvalues on the anisotropy strength of tensor has not been previously addressed in the definition of the speed function. In this article, a new speed function, based on the effect of diffusion anisotropy and the colinearity of eigenvectors is proposed. The performance of the suggested method on fiber tracking and crossing fiber detection has been evaluated using synthetic datasets, and the feasibility of the proposed method was shown by fiber tracking implemented on real DTI data. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 307–314, 2011     

Watermarking in halftone images with noise balance strategy

Two novel and robust methods for embedding watermarks into error‐diffused halftone images are presented in this study. The first method is referred to as Dither‐Referenced Error Diffusion (DREDF), where the proposed Average Ordered Dithering (AOD) is adopted to produce the referenced halftone image. The Noise‐ Balanced Error diffusion (NBEDF) is then applied to embed the watermark. The other method is referred to as Parity‐Matched Error Diffusion (PMEDF). This approach achieves good image quality and capacity as high as 6.25 to 25%. Since the two techniques are blind, the decoder does not need any priori knowledge of the original halftone image or watermark. The capacity of the two approaches is also flexible to accommodate all kinds of applications. As the experimental results demonstrated, both techniques are able to guard against degradation due to cropping, tampering, and the print‐and‐scan process in error‐diffused halftone images. Moreover, both methods have features of low computational complexity, low memory demand, and good image quality. © 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 202–214, 2010.     

On the enhancement of low‐order mixed finite element methods for the large deformation analysis of diffusion in solids

A stabilized scheme is developed for mixed finite element methods for strongly coupled diffusion problems in solids capable of large deformations. Enhanced assumed strain techniques are employed to cure spurious oscillation patterns of low‐order displacement/pressure mixed formulations in the incompressible limit for quadrilateral elements and brick elements. A study is presented that shows how hourglass instabilities resulting from geometrically nonlinear enhanced assumed strain methods have to be distinguished from pressure oscillation patterns due to the violation of the inf‐sup condition. Moreover, an element formulation is proposed that provides stable results with respect to both types of instabilities. Comparisons are drawn between material models for incompressible solids of Mooney–Rivlin type and models for standard diffusion in solids with incompressible matrices such as polymeric gels. Representative numerical examples underline the ability of the proposed element formulation to cure instabilities of low‐order mixed formulations. Copyright © 2015 John Wiley & Sons, Ltd.     

Watermarking in halftone images with mixed halftone techniques

Ordered dithering and error diffusion are the two most popular processes to produce halftone results for printing industry. Ordered dithering inherently has the benefit of efficiency. On the other hand, error diffusion has high quality and reasonable complexity. In this article, we propose a watermarking that adopts the ordered dithering to produce the referenced halftone image, then applying the noise‐balanced error diffusion to embed the watermark. A low computational complexity, low memory demand, and good embedded image quality are achieved with the proposed technique. From the experimental results, this technique can guard against the cropping and print‐and‐scan two major degradation processes in halftone images. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 303–314, 2007     

A medical image enhancement method using adaptive thresholding in NSCT domain combined unsharp masking

In the process of medical image formation, the medical image is often interfered by various factors, and it is deteriorated by some new noise that may reduce the quality of the obtained image, which affect the clinical diagnosis seriously. A new medical image enhancement method is proposed in this article. Firstly, the initial medical image is decomposed into the NSCT domain with a low‐frequency sub‐band, and several high‐frequency sub‐bands. Secondly, linear transformation is adopted for the coefficients of the low‐frequency sub‐band. An adaptive thresholding method is used for denoising the coefficients of the high‐frequency sub‐bands. Then, all sub‐bands were reconstructed into spatial domains using the inverse transformation of NSCT. Finally, unsharp masking was used to enhance the details of the reconstructed image. The results of experiment show that the proposed method is superior to other methods in image entropy, EME, and PSNR. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 199–205, 2015     

Medical image fusion based on nuclear norm minimization

Medical image fusion plays an important role in diagnosis and treatment of diseases such as image‐guided radiotherapy and surgery. Although numerous medical image fusion methods have been proposed, most approaches have not touched the low rank nature of matrix formed by medical image, which usually lead to fusion image distortion and image information loss. These methods also often lack universality when dealing with different kinds of medical images. In this article, we propose a novel medical image fusion to overcome aforementioned issues on existing methods with the aid of low rank matrix approximation with nuclear norm minimization (NNM) constraint. The workflow of our method is described as: firstly, nonlocal similar patches across the medical image are searched by block matching for local patch in source images. Second, a fused matrix is stacking by shared nonlocal similarity patches, then the low rank matrix approximation methods under nuclear norm minimization can be used to recover low rank feature of fused matrix. Finally, fused image can be gotten by aggregating all the fused patches. Experimental results show that the proposed method is superior to other methods in both subjectively visual performance and objective criteria. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 310–316, 2015     

Revealing the Atomic Origin of Heterogeneous Li‐Ion Diffusion by Probing Na

Tracing the dynamic process of Li‐ion transport at the atomic scale has long been attempted in solid state ionics and is essential for battery material engineering. Approaches via phase change, strain, and valence states of redox species have been developed to circumvent the technical challenge of direct imaging Li; however, all are limited by poor spatial resolution and weak correlation with state‐of‐charge (SOC). An ion‐exchange approach is adopted by sodiating the delithiated cathode and probing Na distribution to trace the Li deintercalation, which enables the visualization of heterogeneous Li‐ion diffusion down to the atomic level. In a model LiNi_1/3Mn_1/3Co_1/3O₂ cathode, dislocation‐mediated ion diffusion is kinetically favorable at low SOC and planar diffusion along (003) layers dominates at high SOC. These processes work synergistically to determine the overall ion‐diffusion dynamics. The heterogeneous nature of ion diffusion in battery materials is unveiled and the role of defect engineering in tailoring ion‐transport kinetics is stressed.     

Simple image intensity compensation (SIMIC) method prior to application of distortion correction algorithms in brain diffusion Tensor Magnetic Resonance Imaging: Validation test for two cost functions of distortion correction algorithms

The purpose of this study is to design a simple image intensity compensation (SIMIC) method prior to the application of a variety of cost functions for distortion correction in diffusion tensor imaging (DTI). The synthetic dataset consists of each direction of diffusion weighted imaging (DWI) made by multiplication of nondiffusion weighted image (b = 0 image) and tensor matrices. We added the effects of patient motion and eddy current distortion using translation, rotation, scaling and shearing matrices. We calculated the b = 0 image of each direction from original DTI, inversely. A co‐registration method was applied to the extracted b = 0 images of each direction based on the original b = 0 image and then, the transformation matrices were generated and the original DTI were transformed using this transformation matrix. For the DTI distortion correction, two kinds of cost functions, normalized mutual information (NMI) and normalized cross‐correlation (NCC), were used. Visual assessments and quantitative measurements were used to evaluate the results. When using the NMI as a cost function, the quantitative results showed no significant differences between NMI and NMI with SIMIC method. However, there are significant differences compared with using the NCC as a cost function. Our study showed cost function for image distortion correction with SIMIC method improved the results both quantitatively and in terms of qualitative accuracy. This method may be helpful for DTI analysis and helpful for increasing accuracy. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 328–33, 2015     

A dual domain decomposition method for finite element digital image correlation

The computational burden associated to finite element based digital image correlation methods is mostly due to the inversion of finite element systems and to image interpolations. A non‐overlapping dual domain decomposition method is here proposed to rationalise the computational cost of high resolution finite element digital image correlation measurements when dealing with large images. It consists in splitting the global mesh into submeshes and the reference and deformed states images into subset images. Classic finite element digital image correlation formulations are first written in each subdomain independently. The displacement continuity at the interfaces is enforced by introducing a set of Lagrange multipliers. The problem is then condensed on the interface and solved by a conjugate gradient algorithm. Three different preconditioners are proposed to accelerate its convergence. The proposed domain decomposition method is here exemplified with real high resolution images. It is shown to combine the metrological performances of finite element based digital image correlation and the parallelisation ability of subset based methods. Copyright © 2015 John Wiley & Sons, Ltd.     

Image‐based model reconstruction and meshing of woven reinforcements in composites

A method based on dual kriging is proposed to process X‐ray microtomographic scans of textile composites in order to construct a 3D representation of the fiber architecture with a regulated level of details. The geometry is optimized by using the curvature energy of fiber tow profiles in order to determine the best discretization scheme; then the nugget effect is applied in kriging to smooth the outward surface of fiber tows. This approach allows creating 3D models of variable resolution ranging from the X‐ray scan level to geometric representations with surface meshes required for numerical simulation. The method is applied to a glass fiber textile laminate embedded in a thermoplastic matrix, and preliminary results for the estimation of the local permeability of the fiber tows are presented. Copyright © 2017 John Wiley & Sons, Ltd.     

Improving performance of wavelet-based image de-noising algorithm using complex diffusion process

Abstract

Image enhancement and de-noising is an essential pre-processing step in many image processing algorithms. In any image de-noising algorithm, the main concern is to keep the interesting structures of the image. Such interesting structures often correspond to the discontinuities (edges). In this paper, we present a new algorithm for image noise reduction based on the combination of complex diffusion process and wavelet thresholding. In the existing wavelet thresholding methods, the noise reduction is limited, because the approximate coefficients containing the main information of the image are kept unchanged. Since noise affects both the approximate and detail coefficients, the proposed algorithm for noise reduction applies the complex diffusion process on the approximation band in order to alleviate the deficiency of the existing wavelet thresholding methods. The algorithm has been examined using a variety of standard images and its performance has been compared against several de-noising algorithms known from the prior art. Experimental results show that the proposed algorithm preserves the edges better and in most cases, improves the measured visual quality of the de-noised images in comparison to the existing methods known from the literature. The improvement is obtained without excessive computational cost, and the algorithm works well on a wide range of different types of noise.     

Medical image fusion based on improved sum‐modified‐Laplacian

Sum‐modified‐Laplacian (SML) plays an important role in medical image fusion. However, fused rules based on larger SML always lead to fusion image distortion in transform domain image fusion or image information loss in spatial domain image fusion. Combined with average filter and median filter, a new medical image fusion method based on improved SML (ISML) is proposed. First, a basic fused image is gained by ISML, which is used for evaluation of the selection map of medical images. Second, difference images can be obtained by subtracting average image of all sources of medical images. Finally, basic fused image can be refined by difference images. The algorithm can both preserve the information of the source images well and suppress pixel distortion. Experimental results demonstrate that the proposed method outperforms the state‐of‐the‐art medical image fusion methods. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 206–212, 2015     

A Comparative Study of Enhanced Infrared Image Processing for Foreign Object Detection in Lightweight Composite Honeycomb Structures

The interest toward lightweight composites in the aeronautical industry grows year by year. The challenge is the identification and characterization of defects by using an integration of different techniques. The use of the infrared thermography (IRT) method for the inspection of lightweight composites is poorly documented in the open literature, due to the low heat diffusion through the honeycomb cores. In this study, IRT was used to retrieve the unknown positions of internal inserted objects in three different lightweight composite structures, by using three new thermal image processing integration methods. The corresponding post-processed results were compared against the traditional principal component thermography and pulsed phase thermography image processing techniques. The comparison showed that the integrated signal smoothing processing enhanced the image quality compared to the established techniques. Then, a thermal-physical analysis corresponding to the experimental results was conducted, in order to explain the experimental results. Finally, the advantages and disadvantages of the different presented methods when applied on the different lightweight composite structures were summarized.     

Adaptive spacetime discontinuous Galerkin method for hyperbolic advection–diffusion with a non‐negativity constraint

Applications where the diffusive and advective time scales are of similar order give rise to advection–diffusion phenomena that are inconsistent with the predictions of parabolic Fickian diffusion models. Non‐Fickian diffusion relations can capture these phenomena and remedy the paradox of infinite propagation speeds in Fickian models. In this work, we implement a modified, frame‐invariant form of Cattaneo's hyperbolic diffusion relation within a spacetime discontinuous Galerkin advection–diffusion model. An h‐adaptive spacetime meshing procedure supports an asynchronous, patch‐by‐patch solution procedure with linear computational complexity in the number of spacetime elements. This localized solver enables the selective application of optimization algorithms in only those patches that require inequality constraints to ensure a non‐negative concentration solution. In contrast to some previous methods, we do not modify the numerical fluxes to enforce non‐negative concentrations. Thus, the element‐wise conservation properties that are intrinsic to discontinuous Galerkin models are defined with respect to physically meaningful Riemann fluxes on the element boundaries. We present numerical examples that demonstrate the effectiveness of the proposed model, and we explore the distinct features of hyperbolic advection–diffusion response in subcritical and supercritical flows. Copyright © 2015 John Wiley & Sons, Ltd.     

Image SR-based NLM and DCNN improved IBP with cubic B-spline

ABSTRACT

Image super-resolution (SR) techniques aim to estimate high-resolution (HR) image from low-resolution (LR) image. Existing SR method has slow convergence and recovery of high-frequency details are inaccurate. To overcome these issues, two algorithms have been proposed for image SR based on non-local means improved iterative back projection (NLM-IIBP), deep convolutional neural network improved iterative back projection (DCNN-IIBP) to produce high-resolution images with low noise, minimal blur by restoring high-frequency details. In NLM-IIBP denoised images have been interpolated using cubic B-spline interpolation and processed using IIBP based on guided bilateral method. NLM preserves the edges effectively, but does not consider high dimensional information and over smoothing during noise minimization. To further improve the resolution, NLM is replaced by DCNN. DCNN denoising method suppresses different noises at different noise levels. The proposed algorithms have been analysed and compared with existing approaches using various parameters to prove the effectiveness.     

Extended finite element method coupled with face‐based strain smoothing technique for three‐dimensional fracture problems

In this work, the extended finite element method (XFEM) is for the first time coupled with face‐based strain‐smoothing technique to solve three‐dimensional fracture problems. This proposed method, which is called face‐based smoothed XFEM here, is expected to combine both the advantages of XFEM and strain‐smoothing technique. In XFEM, arbitrary crack geometry can be modeled and crack advance can be simulated without remeshing. Strain‐smoothing technique can eliminate the integration of singular term over the volume around the crack front, thanks to the transformation of volume integration into area integration. Special smoothing scheme is implemented in the crack front smoothing domain. Three examples are presented to test the accuracy, efficiency, and convergence rate of the face‐based smoothed XFEM. From the results, it is clear that smoothing technique can improve the performance of XFEM for three‐dimensional fracture problems. Copyright © 2015 John Wiley & Sons, Ltd.     

Smoothing Measured Displacements and Computing Strains Utilising Finite Element Method

Abstract: A method for smoothing measured displacements and computing strains utilising finite element and least‐squares methods is proposed. Nodal displacement values of a finite element model are determined by fitting the interpolation functions of elements to measured displacement values using the method of least‐squares. The displacements in the region where the measurement values are not obtained or unreliable are determined by solving finite element equations. Then, strains are obtained using a displacement‐strain relationship. The validity is demonstrated by applying the proposed method to the displacement distributions of a plate with a hole obtained using finite element method and those around a crack tip obtained using digital image correlation. Results show that the displacements and the strains can be determined accurately by the proposed method. Furthermore, the strains near free boundaries and strain concentration region can be computed. As strains can be evaluated easily and accurately, the proposed method can be used as one of the data processing methods for optical methods.     

On the problem of gradient calibration in diffusion weighted imaging

A calibration method for diffusion‐weighted imaging using an isotropic phantom is proposed. The key point of the method consists in finding optimized balancing times for different orientations of diffusion‐encoding gradients followed by retrospective rescaling of the diffusion‐weighted images. The correction protocol was applied to produce improved fractional anisotropy maps which were analyzed with statistical histograms. The results demonstrate that the described scheme of systematic error reduction is a valid approach for quality control studies of gradient system performance for diffusion‐weighted imaging. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 271–279, 2011;