Regularization in parallel magnetic resonance imaging

SPIRiT (iterative self‐consistent parallel imaging reconstruction) can be solved efficiently for data acquired on arbitrary k‐space trajectories, and its sparsity regularized variant L1‐SPIRiT accelerates reconstruction. In this paper, we propose a regularized SPIRiT reconstruction based on steerable pyramid decomposition. The directionally filter banks lead to a better separation of signal and noise compared to a discrete wavelet transform (DWT). In vivo datasets and eight‐channel Shepp‐Logan phantom studies demonstrate efficient reconstructions. We compared our work with five state‐of‐the‐art parallel imaging techniques; our method yields better reconstruction results.     

Iron-based magnetic nanoparticles for magnetic resonance imaging

Magnetic resonance imaging (MRI) has been an extensive area of research owing to its depth of penetration for clinical diagnosis. Signal intensity under MRI is related to both T₁, spin-lattice relaxation, and T₂, spin-spin relaxation. To increase the contrast variability under MRI, several contrast agents are being used, i.e. T₁ contrast agents (e.g. gadolinium) and T₂ contrast agents (e.g. iron-based magnetic nanoparticles). These contrast agents are administered prior to scanning to increase contrast visibility. They reduce the T₁ and T₂ relaxation times to produce hyperintense and hypointense signals, respectively. Tunable properties of iron-based magnetic nanoparticles and several coating materials provide a platform to get superb MRI contrast in T₂ weighted images. It has been found that contrast enhancement by iron-based magnetic nanoparticles is dependent on the size, shape, composition, surface, and magnetic properties which can be tuned with the synthesis method and coating material. Therefore, understanding the synthesis method and properties of magnetic nanoparticles is vital to contribute to MR signal enhancement which is directing the scientist to design engineered iron-based magnetic nanoparticles. This paper introduces the concept of MRI contrast enhancement. We mainly discuss the synthesis of T₂ contrast agents, i.e. iron-based magnetic nanoparticles and the modification of these T₂ contrast agents by coating followed by their biomedical applications.     

无损检测在木材应用中的现状及发展趋势

无损检测技术在木材检测中的地位日益重要,本文主要从应力波检测、超声波检测、X射线检测和机械应力检测四个方面介绍了无损检测在木材中的应用,阐述了其基本原理和特点,概述了发展历史和研究现状,并展望了未来研究方向及工作重点。     

Application of magnetic resonance imaging techniques to particulate systems

Magnetic resonance imaging (MRI) is a well-established technique in the medical field, typically for imaging liquid water in the human body, but it is increasingly being used in the field of engineering and materials science. A particular section of this is in the area of particulate systems and granular material flows. MRI is being used to provide a unique insight into particle distribution and motion with in situ measurements. In this paper we discuss how judicious choice and development of imaging technique applied to various different granular systems can provide us with valuable new data on the processes occurring in granular flows. Experimental results focus on rotating bed segregation, velocity imaging in vertical fluidized beds and phase-resolved velocity distributions within vertical vibro-fluidized beds. A discussion of the various imaging techniques used to acquire these data is also given.     

Demonstration of nuclear magnetic resonance imaging for void detection in carbon-fibre reinforced polymer composites,and comparison with ultrasound methods

Nuclear magnetic resonance imaging has been used as a method of void detection in carbonfibre reinforced polymer composites. This is accomplished by observation of signal from water molecules which have ingressed into surface-connected defect regions within the polymer composite. Problems associated with the conductivity of these samples are discussed, along with methods of overcoming those difficulties.     

Overview of non-destructive evaluation techniques for metal-based additive manufacturing

Three-dimensional printing/digital or additive manufacturing is an area that is taking off with considerable rapidity and magnitude. In the same time, non-destructive evaluation (NDE) is playing an important role in the acceptance of additively manufactured parts, in order to provide the required confidence in the quality of the part and its expected safety and performance while in service. This article represents a summary addressing the subject of applicable NDE techniques to detect manufacturing anomalies and service-induced flaws. The topic is relatively new, attracting much research attention and funding, while in the meantime manufacturing processes are continuously improving. The number of publications covering additive manufacturing is increasing exponentially, and everyday new articles, conferences, and workshops are bringing out new information.     

Non-destructive monitoring of creaming of oil-in-water emulsion-based formulations using magnetic resonance imaging

A non-destructive method for monitoring creaming of emulsion-based formulations is in great demand because it allows us to understand fully their instability mechanisms. This study was aimed at demonstrating the usefulness of magnetic resonance (MR) techniques, including MR imaging (MRI) and MR spectroscopy (MRS), for evaluating the physicochemical stability of emulsion-based formulations. Emulsions that are applicable as the base of practical skin creams were used as test samples. Substantial creaming was developed by centrifugation, which was then monitored by MRI. The creaming oil droplet layer and aqueous phase were clearly distinguished by quantitative MRI by measuring T₁ and the apparent diffusion coefficient. Components in a selected volume in the emulsions could be analyzed using MRS. Then, model emulsions having different hydrophilic–lipophilic balance (HLB) values were tested, and the optimal HLB value for a stable dispersion was determined. In addition, the MRI examination enables the detection of creaming occurring in a polyethylene tube, which is commonly used for commercial products, without losing any image quality. These findings strongly indicate that MR techniques are powerful tools to evaluate the physicochemical stability of emulsion-based formulations. This study will make a great contribution to the development and quality control of emulsion-based formulations.     

Characteristics of a single jet injected into an incipiently fluidized bed: A magnetic resonance imaging study

Rapid magnetic resonance imaging (MRI) was used to characterize properties of a single central gas jet injected into a 3D gas fluidized bed under incipient fluidization conditions. Snapshots of both particle concentration and particle velocity are provided. The average jet height, oscillations in jet height and the size of bubbles breaking off from the jet increased with increasing jet velocity. The frequency of bubble breakoff from the jet decreased with increasing jet velocity. The jet height measurements are compared with various correlations in the literature, and the quantitative data provided here can be compared directly with that from numerical simulations and theoretical predictions for validation purposes.     

Smart nanoprobes for ultrasensitive detection of breast cancer via magnetic resonance imaging

Antibody-conjugated hydrophilic magnetic nanocrystals for use as smart nanoprobes were developed for ultrasensitive detection of breast cancer via magnetic resonance (MR) imaging. MnFe(2)O(4) nanocrystals (MNCs) for use as MR imaging contrast agents were synthesized by thermal decomposition to take advantage of their MR signal enhancement effect. The MNC surfaces were then modified with amphiphilic tri-block copolymers (dicarboxy poly(ethylene glycol)-block-poly(propylene glycol)-block-poly(ethylene glycol)), not only allowing the MNCs to transfer from the organic to the aqueous phase, but also increasing the colloidal stability of the MNCs by masking poly(ethylene glycol). The physicochemical properties of the synthesized hydrophilic magnetic nanocrystals (HMNCs) were fully investigated. Trastuzumab (TZ), a monoclonal antibody against human epidermal growth factor receptor (HER2/neu), was further conjugated on the surface of HMNCs to specifically target HER2/neu over-expressed breast cancer cells. MR imaging analysis of target cells treated with TZ-conjugated HMNCs (TZ-HMNCs) clearly demonstrated their potential as high-performance nanoprobes for selective imaging.     

Using a convolutional neural network model to derive imaging landmarks for lumbar spine numbering on axial magnetic resonance images

Understanding the axial lumbar spine anatomy, including knowledge of the relationship between the lumbar spine level and other paraspinal structures, is important for diagnosing and treating diseases. The purpose of this study was to validate the accuracy of a convolutional neural network (CNN) model in lumbar spine level numbering on axial magnetic resonance (MR) images and to find the appropriate anatomic landmarks for numbering using a class activation map (CAM). A total of 6055 axial MR images of the lumbar spine from the L1-2 to L5-S1 disc levels were obtained to train and validate the CNN model. MR images were acquired using three 3-Tesla machines. The algorithm was developed with three models, and the best-performing model was selected. The external validation set (n = 493) was obtained from other institutions using various machines. The accuracy of the numbering was analyzed using a confusion matrix and receiver operating characteristic curves. The CAMs were reviewed, and the identified anatomic structures were investigated. A reader study was performed by three radiologists, and their accuracy was compared with that of the model. The overall accuracy of the best-performing model for lumbar spine numbering was 0.98 on internal validation and 0.95 on external validation. For the CAM review, mappings concentrated on both paraspinal areas, including the kidney, back muscles, and ilium according to the level. Top-1 and top-2 accuracies of the reviewers ranged between 0.56–0.75, and 0.84–0.93, respectively. After reviewing the CAMs, the accuracy increased to 0.75–0.78 and 0.93–0.98, respectively. A CNN model can accurately determine the level of the lumbar spine on axial MR images, and the configuration of muscles can be used to determine the lumbar level.     

A non-destructive method to determine stresses in a three-dimensional photoelastic model using a transmission polariscope

The determination of stresses within a loaded three dimensional photoelastic model without cutting it into slices has been the ultimate aim of many investigators. The standard methods using a transmission polariscope do not yield much information. Scattered light methods no doubt enable one to completely determine the state of stress at a point within the body. However, the methods proposed up to now necessitate the use of an arrangement where both the body under test and the sensing unit which picks up the scattered light or both will have to be rotated. This leads to a complicated experimental set-up and increases the possibility of making errors, especially while rotating the model. In the proposed method, most of the information needed to determine the state of stress at a point within the body is obtained using the transmission polariscope set-up. The model and the direction of observation of scattered light are fixed. This allows observations to be made in test models which have at least one flat face without using a liquid with matched refractive index and increases the accuracy of measurements. The method is an almost purely transmission polariscope type of method and where space permits tests can be done using 'live' loading without having to use the stress freezing technique.     

Quantitative analysis of cerebrospinal fluid flow in complex regions by using phase contrast magnetic resonance imaging

To develop a method for segmenting cerebrospinal fluid (CSF) regions with complex, inhomogeneous pulsatile patterns in phase contrast magnetic resonance imaging (PC‐MRI) sequences. Our approach used various temporal features of flow behavior as input attributes in an unsupervised k‐means classification algorithm. CSF flow parameters for the cervical subarachnoid spaces and the pontine cistern were calculated in 26 healthy volunteers. Background and aliasing corrections were applied automatically. The algorithm's reproducibility was determined by calculating two parameters (area and stroke volume) while varying the initially selected seed point. The influence of background correction on these parameters was also assessed. The method was highly reproducible, with coefficients of variation of 3 and 4% for the cervical stroke volume and area, respectively. In an analysis of variance, background correction did not have a statistically significant effect on either the stroke volume (p = 0.32) or the CSF net mean flow (p = 0.69) at the C2C3 level. The method presented here enables rapid, reproducible, quantitative analysis of CSF flow in complex regions such as the C2C3 subarachnoid spaces and the pontine cistern. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 290–297, 2011;     

Direct detection of hydrocarbon displacement in a model porous soil with magnetic resonance imaging

The direct detection of hydrocarbon fluid and the discrimination of water through carbon-13 magnetic resonance imaging (MRI) would be a significant advance in many scientific fields including food, petrogeological, and environmental sciences. Carbon-13 MRI is a noninvasive analytical technique that has great potential for direct detection of hydrocarbons. However, the low natural abundance of carbon-13, low gyromagnetic ratio, and generically short transverse signal lifetimes in realistic porous media all conspire to hinder carbon-13 MRI. A multiple echo pure phase encode MRI technique introduced in this paper helps to overcome these limitations. As a pure phase encode technique, it is immune to artifacts arising from inhomogeneous B0 fields. It is also, by its nature, more quantitative than most MRI methods. Viscous hydrocarbon flow through a sand bed, a simple realistic porous medium, was used as our test system. Flow in this model system was driven by capillary suction. The detection limit, spatially resolved, was determined to be 26 mg.     

Linear array arrangement using composite right-/left-handed transmission lines for magnetic resonance imaging

Array coils for magnetic resonance imaging have been used to improve field uniformity, improve signal-to-noise ratios, and increase imaging speed. Alternative radio frequency (RF) coils that use metamaterials, such as loop or microstrip coils, have recently been proposed and are expected to provide better performance than the traditional RF array coils. Transmission lines (TLs) based on metamaterials are known as composite right- and left-handed (CRLH) TLs, which are artificially created by adding inductances and capacitances to a common TL. CRLH TLs have a zero-order resonance mode, wherein wave propagation is independent of the TL's electrical length. Decoupling between array elements is important for obtaining the benefits of parallel imaging. In this study, we analyze the decoupling properties between two CRLH TLs. In addition, we design a linear array of four CRLH TLs to obtain a uniform magnetic (|B₁|)-field in the axial- and longitudinal-direction at 7T for the corresponding frequency of 300 MHz.     

Multiclassifier for severity-level categorization of glioma tumors using multimodal magnetic resonance imaging brain images

Brain tumor segmentation and classification is a crucial challenge in diagnosing, planning, and treating brain tumors. This article proposes an automatic method that categorizes the severity level of the tumors to render an effective diagnosis. The proposed fractional Jaya optimizer-deep convolutional neural network undergoes the severity classification based on the features obtained from the segments of the magnetic resonance imaging (MRI) images. The segments are obtained using the particle swarm optimization that ensures the optimal selection of the segments from the MRI image and yields the core tumor and the edema tumor regions. The experimentation using the BRATS database reveals that the proposed method acquired a maximal accuracy, specificity, and sensitivity of 0.9414, 0.9429, and 0.9708, respectively.     

Thermometric detection of nuclear magnetic resonance

Nuclear magnetic resonance has been detected in nonmagnetic materials by observing the temperature rise in the sample. The experiments were performed at temperatures between 1 and 4 K, and results are presented for the²⁷Al resonance in aluminum metal and the¹⁹F resonance in a sample of doped CaF₂. The primary sources of noise have been identified and ways of improving the apparatus are discussed. The technique could prove useful in experiments that require a large range of frequencies to be swept and in experiments investigating the effects of strong rf fields.     

Multiorgan motion tracking in dynamic magnetic resonance imaging for evaluation of pelvic system mobility and shear strain

Female pelvic disorders have a large social impact; the diagnosis of which relies on a key indication: pelvic mobility. The normal mobility is present in a healthy patient, meanwhile the hypermobility can be a sign of female pelvic prolapse and the hypomobility for endometriosis. The evaluation of pelvic mobility is based on medical image analysis. However, the latter does not provide precise values of these indicators directly. Moreover, suspension devices play an important role in pelvic organ function but can hardly be observed on medical images. Our objective is to propose an image‐based analysis tool for the quantitative evaluation of pelvic mobility and the shear strain which has an impact on suspension devices. Hence, this paper introduces a such tool based on an efficient and semiautomatic motion tracking of multiple pelvic organs: the bladder, vagina, and rectum presented in dynamic magnetic resonance imaging sequences. The method was validated on prototypical images and applied to different mobility cases. The computed displacement and shear strain fields provide important information on the quality of suspension devices between organs for a fine diagnosis in the clinical context, for example, the early diagnosis of female pelvic prolapse and the localization of possible lesion areas before surgery. Meanwhile, the predicted mobility can be used to compare with the finite element model for numerical simulation.