Medical image registration‐based retrieval using distance metrics

In this article, registration and retrieval are carried out separately for medical images and then registration‐based retrieval is performed. It is aimed to provide a more thorough insight on the use of registration, retrieval, and registration‐based retrieval algorithm for medical images. The purpose of this work is to deal these techniques with anatomical imaging modalities for clinical diagnosis, treatment, intervention, and surgical planning in a more effective manner. Two steps are implemented. In the first step, the affine transformation‐based registration for medical image is processed. The second step is the retrieval of medical images processed by using seven distance metrics such as euclidean, manhattan, mahalanobis, canberra, bray‐curtis, squared chord, chi‐squared, and also by using the features like mean, standard deviation, skewness, energy, and entropy. Now images registered by affine transformation are applied for retrieval. In this work, both registration and retrieval techniques in medical domain share some common image processing steps and required to be integrated in a larger system to complement each other. Experimental results, it is evident that euclidean and manhattan produces 100% precision and 35% recall found to have higher performance in retrieval. From the four anatomical modalities considered (brain, chest, liver, and limbs) brain image has better registration. It is also found that though the registration of images changes the orientation, for better performance of images in clinical evaluation it does not widely affect the retrieval performance. In the medical domain the ultimate aim of this work is to provide diagnostic support to physicians and radiologists by displaying relevant past cases, along with proven pathologies as ground truth from experimental results. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 360–371, 2013     

Content‐based gastric image retrieval using convolutional neural networks

The endoscopy procedure has demonstrated great efficiency in detecting stomach lesions, with extensive numbers of endoscope images produced globally each day. The content‐based gastric image retrieval (CBGIR) system has demonstrated substantial potential in gastric image analysis. Gastric precancerous diseases (GPD) have higher prevalence in gastric cancer patients. Thus, effective intervention is crucial at the GPD stage. In this paper, a CBGIR method is proposed using a modified ResNet‐18 to generate binary hash codes for a rapid and accurate image retrieval process. We tested several popular models (AlexNet, VGGNet and ResNet), with ResNet‐18 determined as the optimum option. Our proposed method was valued using a GPD data set, resulting in a classification accuracy of 96.21 ± 0.66% and a mean average precision of 0.927 ± 0.006 , outperforming other state‐of‐art conventional methods. Furthermore, we constructed a Gastric‐Map (GM) based on feature representations in order to visualize the retrieval results. This work has great auxiliary significance for endoscopists in terms of understanding the typical GPD characteristics and improving aided diagnosis.     

An X‐FEM and level set computational approach for image‐based modelling: Application to homogenization

The advances in material characterization by means of imaging techniques require powerful computational methods for numerical analysis. The present contribution focuses on highlighting the advantages of coupling the extended finite elements method and the level sets method, applied to solve microstructures with complex geometries. The process of obtaining the level set data starting from a digital image of a material structure and its input into an extended finite element framework is presented. The coupled method is validated using reference examples and applied to obtain homogenized properties for heterogeneous structures. Although the computational applications presented here are mainly two‐dimensional, the method is equally applicable for three‐dimensional problems. Copyright © 2010 John Wiley & Sons, Ltd.     

Wavelet‐based adaptive vector quantization for still‐image coding

Wavelet transform coding (WTC) with vector quantization (VQ) has been shown to be efficient in the application of image compression. An adaptive vector quantization coding scheme with the Gold‐Washing dynamic codebook‐refining mechanism in the wavelet domain, called symmetric wavelet transform‐based adaptive vector quantization (SWT‐GW‐AVQ), is proposed for still‐image coding in this article. The experimental results show that the GW codebook‐refining mechanism working in the wavelet domain rather than the spatial domain is very efficient, and the SWT‐GW‐AVQ coding scheme may improve the peak signal‐to‐noise ratio (PSNR) of the reconstructed images with a lower encoding time. © 2002 Wiley Periodicals, Inc. Int J Imaging Syst Technol 12, 166–174, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10024     

An improved label fusion approach with sparse patch‐based representation for MRI brain image segmentation

The multi‐atlas patch‐based label fusion (LF) method mainly focuses on the measurement of the patch similarity which is the comparison between the atlas patch and the target patch. To enhance the LF performance, the distribution probability about the target can be used during the LF process. Hence, we consider two LF schemes: in the first scheme, we keep the results of the interpolation so that we can obtain the labels of the atlas with discrete values (between 0 and 1) instead of binary values in the label propagation. In doing so, each atlas can be treated as a probability atlas. Second, we introduce the distribution probability of the tissue (to be segmented) in the sparse patch‐based LF process. Based on the probability of the tissue and sparse patch‐based representation, we propose three different LF methods which are called LF‐Method‐1, LF‐Method‐2, and LF‐Method‐3. In addition, an automated estimation method about the distribution probability of the tissue is also proposed. To evaluate the accuracy of our proposed LF methods, the methods were compared with those of the nonlocal patch‐based LF method (Nonlocal‐PBM), the sparse patch‐based LF method (Sparse‐PBM), majority voting method, similarity and truth estimation for propagated segmentations, and hierarchical multi‐atlas LF with multi‐scale feature representation and label‐specific patch partition (HMAS). Based on our experimental results and quantitative comparison, our methods are promising in the magnetic resonance image segmentation. © 2017 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 27, 23–32, 2017     

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     

基于字符串匹配技术的图像检索算法

为提高图像检索的效果,提出了一种基于字符串匹配技术的图像检索算法。该算法根据人眼的视觉特性及方块编码(BTC)的原理首先对图像进行分割,构造对表征图像内容有意义的图像特征。在此基础上,根据字符出现的概率对字符表征意义的重要性,把图像特征动态映射成字符串形式,然后采用字符串匹配技术进行图像检索。该算法不仅利用了图像中的边缘及纹理分布,而且将字符串匹配技术引入到图像检索中,在提高检索率的同时又加快了检索速度。实验结果表明,该算法具有较高的检索效率。     

Medical image fusion based on laws of texture energy measures in stationary wavelet transform domain

Medical image fusion is widely used in various clinical procedures for the precise diagnosis of a disease. Image fusion procedures are used to assist real-time image-guided surgery. These procedures demand more accuracy and less computational complexity in modern diagnostics. Through the present work, we proposed a novel image fusion method based on stationary wavelet transform (SWT) and texture energy measures (TEMs) to address poor contrast and high-computational complexity issues of fusion outcomes. SWT extracts approximate and detail information of source images. TEMs have the capability to capture various features of the image. These are considered for fusion of approximate information. In addition, the morphological operations are used to refine the fusion process. Datasets consisting of images of seven patients suffering from neurological disorders are used in this study. Quantitative comparison of fusion results with visual information fidelity-based image fusion quality metric, ratio of spatial frequency error, edge information-based image fusion quality metric, and structural similarity index-based image fusion quality metrics proved the superiority. Also, the proposed method is superior in terms of average execution time to state-of-the-art image fusion methods. The proposed work can be extended for fusion of other imaging modalities like fusion of functional image with an anatomical image. Suitability of the fused images by the proposed method for image analysis tasks needs to be studied.     

An efficient method for estimating soft tissue deformation based on intraoperative stereo image features and point‐based registration

Estimation of soft tissue deformation occurring during image‐guided surgery using an easily implemented and accurate method is necessary. Using a stereo camera, this study focuses on two efficient methods for estimating soft tissue deformation. Two methods were proposed to overcome limitations associated with the typical methods used for estimating soft tissue deformation, such as dependence on accuracy of the operator and indentation of skin. The first method is based on Triclops SDK, and the second method is based on projecting a pattern to acquire P‐Lands (Projected Landmarks). Based on the proposed methods, surface information is acquired in the form of point clouds of surface point coordinates to the submillimeter accuracy. The reconstructed predeformation three‐dimensional (3D) point cloud obtained for each method is registered with a modified iterative closest point algorithm to a postdeformation 3D point cloud obtained from the same region of interest. Results were compared with an MRI–MRI registration method as a control. Results are provided as RMS differences between the initial and final coordinates of corresponding points. The average RMS difference for the typical method is 3.53 mm, that for the Triclops SDK method is 2.32 mm, and that for the P‐Lands projection method is 2.06 mm. The MRI‐MRI registration had an average RMS difference of 1.12 mm. Using MRI‐MRI registration as the gold standard, the average error obtained for the typical method was 2.41 mm, that for the first method was 1.2 mm, and that for the second method was 0.94 mm. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 294–303, 2013     

ANFIS‐EM approach for PET brain image reconstruction

In this article, for the reconstruction of the positron emission tomography (PET) images, an iterative MAP algorithm was instigated with its adaptive neurofuzzy inference system based image segmentation techniques which we call adaptive neurofuzzy inference system based expectation maximization algorithm (ANFIS‐EM). This expectation maximization (EM) algorithm provides better image quality when compared with other traditional methodologies. The efficient result can be obtained using ANFIS‐EM algorithm. Unlike any usual EM algorithm, the predicted method that we call ANFIS‐EM minimizes the EM objective function using maximum a posteriori (MAP) method. In proposed method, the ANFIS‐EM algorithm was instigated by neural network based segmentation process in the image reconstruction. By the image quality parameter of PSNR value, the adaptive neurofuzzy based MAP algorithm and de‐noising algorithm compared and the PET input image is reconstructed and simulated in MATLAB/simulink package. Thus ANFIS‐EM algorithm provides 40% better peak signal to noise ratio (PSNR) when compared with MAP algorithm. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 1–6, 2015     

An approach to calculate the J‐integral by digital image correlation displacement field measurement

This paper presents a combined experimental‐numerical technique for the calculation of the J‐integral as an area integral in cracked specimens. The proposed technique is based on full‐field measurement using digital image correlation (DIC) and the finite element method. The J‐integral is probably the most generalised and widely used parameter to quantify the fracture behaviour of both elastic and elastoplastic materials. The proposed technique has the advantage that it does not require crack length measurements nor is it limited to elastic fracture mechanics, provided that only small scale yielding is present. Evaluated are three test geometries; compact tension, three‐point bend and the double torsion beam. Possible errors and their magnitude and the limitations of the method are considered.     

Subband decomposition strategies for object‐based image coding

In order to attain perfect reconstruction, subband decomposition of arbitrarily shaped objects requires special strategies to deal with the decimation problem. One of the two strategies described in this paper (scheme 1) inserts pixels with amplitudes equal to the mean values of the neighboring ones belonging to the object. The requirement of transmitting (coding) these pixels reduces the coding gain and is avoided by the second strategy (scheme 2) examined in this paper. This strategy determines specific values of the pixels added to the object in such a way that they result in predefined amplitudes after decimation. For this reason, this method outperforms scheme 1. PSNR versus bit rate are presented for two objects. © 2003 Wiley Periodicals, Inc. Int J Imaging Syst Technol 13, 179–187, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10054     

A Risk‐based Approach to Managing Performance‐based Maintenance Contracts

The global trend towards performance‐based maintenance contracting has presented new challenges to maintenance service providers as they are compensated or penalized based on performance outcomes instead of time and materials consumed during maintenance service. The problem becomes more complex when uncertainties exist in reliability performance and maintenance activities of technical systems. In this paper, a general framework for managing performance‐based maintenance contract under risks is proposed. We illustrate our approach with an application in a multi‐echelon multi‐system spare parts control problem. Several different performance measures are considered and a probabilistic constrained optimization problem is formulated from the perspective of the service provider. Hybrid simulation/analytic heuristics are proposed to solve the problem based on the monotonic properties of performance measures. This approach is flexible and can be applied to a wide range of problems with similar properties. Numerical example shows that the probability of violating performance requirements is high if the risk is overlooked. We also provide guidelines on how to apply this approach in practice. Copyright © 2016 John Wiley & Sons, Ltd.     

An energy momentum consistent integration scheme using a polyconvexity‐based framework for nonlinear thermo‐elastodynamics

The present contribution provides a new approach to the design of energy momentum consistent integration schemes in the field of nonlinear thermo‐elastodynamics. The method is inspired by the structure of polyconvex energy density functions and benefits from a tensor cross product that greatly simplifies the algebra. Furthermore, a temperature‐based weak form is used, which facilitates the design of a structure‐preserving time‐stepping scheme for coupled thermoelastic problems. This approach is motivated by the general equation for nonequilibrium reversible‐irreversible coupling (GENERIC) framework for open systems. In contrast to complex projection‐based discrete derivatives, a new form of an algorithmic stress formula is proposed. The spatial discretization relies on finite element interpolations for the displacements and the temperature. The superior performance of the proposed formulation is shown within representative quasi‐static and fully transient numerical examples.     

Feature extraction through generalization of histogram refinement technique for local region‐based object attributes

Content based image retrieval (CBIR) is used to retrieve digital images from large databases. However, the problem of retrieving images on the basis of the contents remains largely unsolved. The proposed method of image retrieval is based on the information provided by histogram analysis of the intensity or grayscale values of images. Some additional properties are also calculated and used that are based on regional characteristics of various objects in the image. The need to retrieve the additional regional properties arises due to the fact that the standard histograms are insensitive to small changes in images. Many images of different types can have similar histograms, because, histograms provide only a coarse characterization of an image. This is the main disadvantage of using histograms. This research is based on the concept of Histogram Refinement (Pass and Zabih, IEEE Workshop Appl Comput Vision ( 1996 ), 96–102). Distributing the grayscale image intensities by splitting the pixels using their intensity values into several classes just like the histogram refinement method can provide an estimate of the object characteristics present in an image. After the calculation of clusters using a color refinement method, the inherent features of each of the clusters is calculated based on the regional properties of the clusters. These additional region based features expound some structural information of the image. Finally, all of these features are used for image retrieval. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 298–306, 2011;     

Post optimization for accurate and efficient reliability‐based design optimization using second‐order reliability method based on importance sampling and its stochastic sensitivity analysis

In this study, a post optimization technique for a correction of inaccurate optimum obtained using first‐order reliability method (FORM) is proposed for accurate reliability‐based design optimization (RBDO). In the proposed method, RBDO using FORM is first performed, and then the proposed second‐order reliability method (SORM) is performed at the optimum obtained using FORM for more accurate reliability assessment and its sensitivity analysis. In the proposed SORM, the Hessian of a performance function is approximated by reusing derivatives information accumulated during previous RBDO iterations using FORM, indicating that additional functional evaluations are not required in the proposed SORM. The proposed SORM calculates a probability of failure and its first‐order and second‐order stochastic sensitivity by applying the importance sampling to a complete second‐order Taylor series of the performance function. The proposed post optimization constructs a second‐order Taylor expansion of the probability of failure using results of the proposed SORM. Because the constructed Taylor expansion is based on the reliability method more accurate than FORM, the corrected optimum using this Taylor expansion can satisfy the target reliability more accurately. In this way, the proposed method simultaneously achieves both efficiency of FORM and accuracy of SORM. Copyright © 2015 John Wiley & Sons, Ltd.     

An isogeometric locking‐free NURBS‐based solid‐shell element for geometrically nonlinear analysis

In this work, we develop an isogeometric non‐uniform rational B‐spline (NURBS)‐based solid‐shell element for the geometrically nonlinear static analysis of elastic shell structures. A single layer of continuous 3D elements through the thickness of the shell is considered, and the order of approximation in that direction is chosen to be equal to two. A complete 3D constitutive relation is assumed. The objective is to develop a highly accurate low‐order element for coarse meshes. We propose an extension of the mixed method of Bouclier et al. [11] to deal with locking in the context of large rotations and large displacements. The main idea is to modify the interpolation of the average through the thickness of the stress components. It is also necessary to stabilize the element in order to avoid the occurrence of spurious zero‐energy modes. This was achieved, for the quadratic version, through the adjunction of artificial elementary stabilization stiffnesses. The result is an element of order 2, which is at least as accurate as standard NURBS shell elements of order 4. Linear and nonlinear test calculations have been carried out along with comparisons with other published NURBS and classical techniques in order to assess the performance of the element. Copyright © 2014 John Wiley & Sons, Ltd.     

A novel scaled boundary finite element formulation with stabilization and its application to image‐based elastoplastic analysis

Digital images are increasingly being used as input data for computational analyses. This study presents an efficient numerical technique to perform image‐based elastoplastic analysis of materials and structures. The quadtree decomposition algorithm is employed for image‐based mesh generation, which is fully automatic and highly efficient. The quadtree cells are modeled by scaled boundary polytope elements, which eliminate the issue of hanging nodes faced by standard finite elements. A novel, simple, and efficient scaled boundary elastoplastic formulation with stablisation is developed. In this formulation, the return‐mapping calculation is only required to be performed at a single point in a polytope element, which facilitates the computational efficiency of the elastoplastic analysis and simplicity of implementation. Numerical examples are presented to demonstrate the efficiency and accuracy of the proposed technique for performing the elastoplastic analysis of high‐resolution images.