ORCID Profile
0000-0002-4310-1421
Current Organisations
King Abdullah University of Science and Technology
,
University of Queensland
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Biomedical Instrumentation | Applied Mathematics | Medicinal and Biomolecular Chemistry | Medical Devices | Condensed Matter Physics | Molecular Medicine | Biomedical Engineering | Biologically Active Molecules | Medical Physics | Biological Physics | Numerical Analysis | Dynamical Systems in Applications | Other Physical Sciences | Simulation and Modelling | Manufacturing Processes and Technologies (excl. Textiles) | Other Engineering | Engineering Instrumentation | Medical Biotechnology Diagnostics (incl. Biosensors) | Health Economics | Electronic and Magnetic Properties of Condensed Matter; Superconductivity |
ANZSRC Socio-Economic Objective (SEO)
Medical Instruments | Human Diagnostics | Expanding Knowledge in Engineering | Computer Hardware and Electronic Equipment not elsewhere classified | Expanding Knowledge in the Medical and Health Sciences | Expanding Knowledge in Technology | Human Pharmaceutical Treatments (e.g. Antibiotics) | Appliances and Electrical Machinery and Equipment | Expanding Knowledge in the Physical Sciences | Expanding Knowledge in the Biological Sciences | Expanding Knowledge in the Mathematical Sciences | Ceramics
Related Links
Publications
Numerical study of ultra‐low field nuclear magnetic resonance relaxometry utilizing a single axis magnetometer for signal detection
Publisher: Wiley
Date: 15-04-2013
DOI: 10.1118/1.4800491
Abstract: This paper investigates optimal placement of a localized single-axis magnetometer for ultralow field (ULF) relaxometry in view of various s le shapes and sizes. The authors used finite element method for the numerical analysis to determine the s le magnetic field environment and evaluate the optimal location of the single-axis magnetometer. Given the different s les, the authors analysed the magnetic field distribution around the s le and determined the optimal orientation and possible positions of the sensor to maximize signal strength, that is, the power of the free induction decay. The authors demonstrate that a glass vial with flat bottom and 10 ml volume is the best structure to achieve the highest signal out of s les studied. This paper demonstrates the importance of taking into account the combined effects of sensor configuration and s le parameters for signal generation prior to designing and constructing ULF systems with a single-axis magnetometer. Through numerical simulations the authors were able to optimize structural parameters, such as s le shape and size, sensor orientation and location, to maximize the measured signal in ultralow field relaxometry.
7T GRE-MRI signal compartments are sensitive to dysplastic tissue in focal epilepsy
Publisher: Elsevier BV
Date: 09-2019
DOI: 10.1016/J.MRI.2019.05.011
Abstract: Ultra-high field magnetic resonance imaging data obtained using a multi-echo gradient echo sequence has been shown to contain information on tissue microstructure. Quantitative assessment of water fraction, relaxation time and frequency shift using multi-compartment signal modelling may help improve our understanding of diseases and disorders affecting the human brain. In this study, we explored tissue microstructure information by analysing voxel compartment water fraction and frequency shifts derived from 7 T multi-echo gradient recalled echo MRI data. We aimed to test whether the parameters of a three compartment model could distinguish the normal cortex from the cortex affected by focal cortical dysplasia. We compartmentalised normal and dysplastic cortical regions in patients diagnosed with focal cortical dysplasia. We found the frequency shift parameter of the shortest T
Copper modulates the large dense core vesicle secretory pathway in PC12 cells
Publisher: Oxford University Press (OUP)
Date: 2013
DOI: 10.1039/C3MT20231C
Abstract: Copper (Cu) is an essential biometal involved in a number of cell functions. Abnormal Cu homeostasis has been identified as a major factor in a number of neurodegenerative disorders. However, little is known about how cells of brain origin maintain Cu homeostasis and in particular, how they respond to an elevated Cu environment. Understanding these processes is essential to obtaining a greater insight into the pathological changes in neurodegeneration and ageing. Although previous studies have shown that Cu in neurons can be associated with synaptic function, there is little understanding of how Cu modulates the regulated secretory vesicle pathways in these cells. In this study, we examined the effect of elevated intracellular Cu on proteins associated with the regulated secretory vesicle pathway in NGF-differentiated PC12 cells that exhibit neuronal-like properties. Increasing intracellular Cu with a cell-permeable Cu-complex (Cu(II)(gtsm)) resulted in increased expression of synaptophysin and robust translocation of this and additional vesicular proteins from synaptic-like microvesicle (SLMV) fractions to chromogranin-containing putative large dense core vesicle (LDCV) fractions in density gradient preparations. The LDCV fractions also contained substantially elevated Cu levels upon treatment of cells with Cu(II)(gtsm). Expression of the H(+) pump, V-ATPase, which is essential for vesicle maturation, was increased in Cu-treated cells while inhibition of V-ATPase prevented translocation of synaptophysin to LDCV fractions. Cu treatment was found to inhibit release of LDCVs in chromaffin cells due to reduced Ca(2+)-mediated vesicle exocytosis. Our findings demonstrate that elevated Cu can modulate LDCV metabolism potentially resulting in sequestration of Cu in this vesicle pool.
Utility of gradient recalled echo magnetic resonance imaging for the study of myelination in cuprizone mice treated with fingolimod
Publisher: Wiley
Date: 20-12-2018
DOI: 10.1002/NBM.3877
Abstract: The availability of high-field-strength magnetic resonance imaging (MRI) systems has brought about the development of techniques that aim to map myelination via the exploitation of various contrast mechanisms. Myelin mapping techniques have the potential to provide tools for the diagnosis and treatment of diseases, such as multiple sclerosis. In this study, we evaluated the sensitivity of T
Intravenous immunoglobulin protects neurons against amyloid beta‐peptide toxicity and ischemic stroke by attenuating multiple cell death pathways
Publisher: Wiley
Date: 27-04-2012
Modified human contrast sensitivity function based phase mask for susceptibility-weighted imaging
Publisher: Elsevier BV
Date: 2014
Effective cell-centred time-domain Maxwell’s equations numerical solvers
Publisher: Elsevier BV
Date: 05-2005
Globally optimal superconducting magnets Part I: Minimum stored energy (MSE) current density map
Publisher: Elsevier BV
Date: 2009
DOI: 10.1016/J.JMR.2008.09.018
Abstract: An optimal current density map is crucial in magnet design to provide the initial values within search spaces in an optimization process for determining the final coil arrangement of the magnet. A strategy for obtaining globally optimal current density maps for the purpose of designing magnets with coaxial cylindrical coils in which the stored energy is minimized within a constrained domain is outlined. The current density maps obtained utilising the proposed method suggests that peak current densities occur around the perimeter of the magnet domain, where the adjacent peaks have alternating current directions for the most compact designs. As the dimensions of the domain are increased, the current density maps yield traditional magnet designs of positive current alone. These unique current density maps are obtained by minimizing the stored magnetic energy cost function and therefore suggest magnet coil designs of minimal system energy. Current density maps are provided for a number of different domain arrangements to illustrate the flexibility of the method and the quality of the achievable designs.
HSQC spectral based similarity matching of compounds using nearest neighbours and a fast discrete genetic algorithm
Publisher: Springer Science and Business Media LLC
Date: 03-10-2012
Assessment of microstructural signal compartments across the corpus callosum using multi-echo gradient recalled echo at 7 T
Publisher: Elsevier BV
Date: 11-2018
DOI: 10.1016/J.NEUROIMAGE.2017.11.029
Abstract: Quantitative assessment of tissue microstructure is important in studying human brain diseases and disorders in which white matter is implicated, as it has been linked to demyelination, re-myelination, and axonal damage in clinical conditions. Ultra-high field magnetic resonance imaging data obtained using a multi-echo gradient echo sequence has been shown to contain information on myelin, axonal and extracellular compartments in white matter. In this study, we aimed to assess the sensitivity of a three-compartment model to estimate the variation of corresponding compartment parameters (water fraction, relaxation time and frequency shift) of the corpus callosum sub-regions, which are known to have different tissue structure. Additionally, we computed the g-ratio using myelin and axonal water fractions and performed a voxel-by-voxel analysis in the corpus callosum. Based on data acquired for ten participants, we show that the myelin compartment water fraction and T
From CNNs to GANs for cross-modality medical image estimation
Publisher: Elsevier BV
Date: 07-2022
DOI: 10.1016/J.COMPBIOMED.2022.105556
Abstract: Cross-modality image estimation involves the generation of images of one medical imaging modality from that of another modality. Convolutional neural networks (CNNs) have been shown to be useful in image-to-image intensity projections, in addition to identifying, characterising and extracting image patterns. Generative adversarial networks (GANs) use CNNs as generators and estimated images are classified as true or false based on an additional discriminator network. CNNs and GANs within the image estimation framework may be considered more generally as deep learning approaches, since medical images tend to be large in size, leading to the need for large neural networks. Most research in the CNN/GAN image estimation literature has involved the use of MRI data with the other modality primarily being PET or CT. This review provides an overview of the use of CNNs and GANs for cross-modality medical image estimation. We outline recently proposed neural networks and detail the constructs employed for CNN and GAN image-to-image synthesis. Motivations behind cross-modality image estimation are outlined as well. GANs appear to provide better utility in cross-modality image estimation in comparison with CNNs, a finding drawn based on our analysis involving metrics comparing estimated and actual images. Our final remarks highlight key challenges faced by the cross-modality medical image estimation field, including how intensity projection can be constrained by registration (unpaired versus paired data), use of image patches, additional networks, and spatially sensitive loss functions.
Minimum stored energy MRI superconducting magnets: From low to high field
Publisher: Wiley
Date: 08-2009
DOI: 10.1002/CMR.B.20143
Characterization of anomalous relaxation using the time-fractional Bloch equation and multiple echo T2*-weighted magnetic resonance imaging at 7 T
Publisher: Wiley
Date: 26-03-2016
DOI: 10.1002/MRM.26222
Abstract: To study the utility of fractional calculus in modeling gradient-recalled echo MRI signal decay in the normal human brain. We solved analytically the extended time-fractional Bloch equations resulting in five model parameters, namely, the litude, relaxation rate, order of the time-fractional derivative, frequency shift, and constant offset. Voxel-level temporal fitting of the MRI signal was performed using the classical monoexponential model, a previously developed anomalous relaxation model, and using our extended time-fractional relaxation model. Nine brain regions segmented from multiple echo gradient-recalled echo 7 Tesla MRI data acquired from five participants were then used to investigate the characteristics of the extended time-fractional model parameters. We found that the extended time-fractional model is able to fit the experimental data with smaller mean squared error than the classical monoexponential relaxation model and the anomalous relaxation model, which do not account for frequency shift. We were able to fit multiple echo time MRI data with high accuracy using the developed model. Parameters of the model likely capture information on microstructural and susceptibility-induced changes in the human brain. Magn Reson Med 77:1485-1494, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
A short 18F-FDG imaging window triple injection neuroimaging protocol for parametric mapping in PET
Publisher: Research Square Platform LLC
Date: 07-06-2023
DOI: 10.21203/RS.3.RS-2806745/V1
Abstract: Background In parametric PET, kinetic parameters are extracted from dynamic PET images. It is not commonly used in clinical practice because of long scan times and the requirement for an arterial input function (AIF). To address these limitations, we designed an 18 F-fluorodeoxyglucose ( 18 F-FDG) triple injection dynamic PET protocol for brain imaging with a standard field of view PET scanner using a 24 min imaging window and an input function modelled using measurements from a region of interest placed over the left ventricle. Methods To test the protocol in 6 healthy participants, we examined the quality of voxel-based maps of kinetic parameters in the brain generated using the two tissue compartment model and compared estimated parameter values with previously published values. We also utilized data from a 36 minute validation imaging window to compare 1) the modelled AIF against the input function measured in the validation window and 2) the net influx rate (\\({K}_{i}\\)) computed using parameter estimates from the short imaging window against the net influx rate obtained using Patlak analysis in the validation window. Results Compared to the AIF measured in the validation window, the input function estimated from the short imaging window achieved a mean area under the curve error of 9%. The voxel-wise Pearson’s correlation between \\({K}_{i}\\) estimates from the short imaging window and the validation imaging window exceeded 0.95. Conclusion The proposed 24 min triple injection protocol enables parametric 18 F-FDG neuroimaging with non-invasive estimation of the AIF from cardiac images using a standard field of view PET scanner.
Investigation of Changes in Anomalous Diffusion Parameters in a Mouse Model of Brain Tumour
Publisher: Springer International Publishing
Date: 2020
Globally optimal, minimum stored energy, double‐doughnut superconducting magnets
Publisher: Wiley
Date: 30-11-2009
DOI: 10.1002/MRM.22189
Abstract: The use of the minimum stored energy current density map-based methodology of designing closed-bore symmetric superconducting magnets was described recently. The technique is further developed to cater for the design of interventional-type MRI systems, and in particular open symmetric magnets of the double-doughnut configuration. This extends the work to multiple magnet domain configurations. The use of double-doughnut magnets in MRI scanners has previously been hindered by the ability to deliver strong magnetic fields over a sufficiently large volume appropriate for imaging, essentially limiting spatial resolution, signal-to-noise ratio, and field of view. The requirement of dedicated interventional space restricts the manner in which the coils can be arranged and placed. The minimum stored energy optimal coil arrangement ensures that the field strength is maximized over a specific region of imaging. The design method yields open, dual-domain magnets capable of delivering greater field strengths than those used prior to this work, and at the same time it provides an increase in the field-of-view volume. Simulation results are provided for 1-T double-doughnut magnets with at least a 50-cm 1-ppm (parts per million) field of view and 0.7-m gap between the two doughnuts.
Tissue microstructure features derived from anomalous diffusion measurements in magnetic resonance imaging
Publisher: Wiley
Date: 18-10-2016
DOI: 10.1002/HBM.23441
Rotatable Small Permanent Magnet Array for Ultra-Low Field Nuclear Magnetic Resonance Instrumentation: A Concept Study
Publisher: Public Library of Science (PLoS)
Date: 06-06-2016
Quadrature radio frequency coil for magnetic resonance imaging of the wrist at 4T
Publisher: Wiley
Date: 28-10-2009
DOI: 10.1002/CMR.B.20146
Toward designing asymmetric head gradient coils for high-resolution imaging
Publisher: Wiley
Date: 2007
DOI: 10.1002/CMR.B.20082
A hybrid technique for computing the power distribution generated in a lossy medium during microwave heating
Publisher: Elsevier BV
Date: 12-2006
Haptic interaction of organs based on the spherical harmonic representation
Publisher: Wiley
Date: 04-2010
DOI: 10.1002/CMR.B.20160
Edge-carboxylated graphene nanosheets via ball milling
Publisher: Proceedings of the National Academy of Sciences
Date: 27-03-2012
Abstract: Low-cost, high-yield production of graphene nanosheets (GNs) is essential for practical applications. We have achieved high yield of edge-selectively carboxylated graphite (ECG) by a simple ball milling of pristine graphite in the presence of dry ice. The resultant ECG is highly dispersable in various solvents to self-exfoliate into single- and few-layer (≤ 5 layers) GNs. These stable ECG (or GN) dispersions have been used for solution processing, coupled with thermal decarboxylation, to produce large-area GN films for many potential applications ranging from electronic materials to chemical catalysts. The electrical conductivity of a thermally decarboxylated ECG film was found to be as high as 1214 S/cm, which is superior to its GO counterparts. Ball milling can thus provide simple, but efficient and versatile, and eco-friendly (CO 2 -capturing) approaches to low-cost mass production of high-quality GNs for applications where GOs have been exploited and beyond.
The application of the distributed-order time fractional Bloch model to magnetic resonance imaging
Publisher: Elsevier BV
Date: 08-2022
A fast multi-resolution differential evolution method for multimodal image registration
Publisher: IEEE
Date: 10-2012
Magnetic susceptibility derived from T2 and T‐weighted magnetic resonance magnitude images
Publisher: Wiley
Date: 02-2012
DOI: 10.1002/CMR.B.21206
Can anomalous diffusion models in magnetic resonance imaging be used to characterise white matter tissue microstructure?
Publisher: Elsevier BV
Date: 07-2018
DOI: 10.1016/J.NEUROIMAGE.2018.03.052
Abstract: During the time window of diffusion weighted magnetic resonance imaging experiments (DW-MRI), water diffusion in tissue appears to be anomalous as a transient effect, with a mean squared displacement that is not a linear function of time. A number of statistical models have been proposed to describe water diffusion in tissue, and parameters describing anomalous as well as Gaussian diffusion have previously been related to measures of tissue microstructure such as mean axon radius. We analysed the relationship between white matter tissue characteristics and parameters of existing statistical diffusion models. A white matter tissue model (ActiveAx) was used to generate multiple b-value diffusion-weighted magnetic resonance imaging signals. The following models were evaluated to fit the diffusion signal: 1) Gaussian models - 1a) mono-exponential decay and 1b) bi-exponential decay 2) Anomalous diffusion models - 2a) stretched exponential, 2b) continuous time random walk and 2c) space fractional Bloch-Torrey equation. We identified the best candidate model based on the relationship between the diffusion-derived parameters and mean axon radius and axial diffusivity, and applied it to the in vivo DW-MRI data acquired at 7.0 T from five healthy participants to estimate the same selected tissue characteristics. Differences between simulation parameters and fitted parameters were used to assess accuracy and in vivo findings were compared to previously reported observations. The space fractional Bloch-Torrey model was found to be the best candidate in characterising white matter on the base of the ActiveAx simulated DW-MRI data. Moreover, parameters of the space fractional Bloch-Torrey model were sensitive to mean axon radius and axial diffusivity and exhibited low noise sensitivity based on simulations. We also found spatial variations in the model parameter β to reflect changes in mean axon radius across the mid-sagittal plane of the corpus callosum. Simulations have been used to define how the parameters of the most common statistical magnetic resonance imaging diffusion models relate to axon radius and diffusivity. The space fractional Bloch-Torrey equation was identified as the best model for the characterisation of axon radius and diffusivity. This model allows changes in mean axon radius and diffusivity to be inferred from spatially resolved maps of model parameters.
Fast parallel image reconstruction using smacker for functional magnetic resonance imaging
Publisher: IEEE
Date: 05-2008
Globally optimal superconducting magnets Part II: Symmetric MSE coil arrangement
Publisher: Elsevier BV
Date: 2009
DOI: 10.1016/J.JMR.2008.09.023
Abstract: A globally optimal superconducting magnet coil design procedure based on the Minimum Stored Energy (MSE) current density map is outlined. The method has the ability to arrange coils in a manner that generates a strong and homogeneous axial magnetic field over a predefined region, and ensures the stray field external to the assembly and peak magnetic field at the wires are in acceptable ranges. The outlined strategy of allocating coils within a given domain suggests that coils should be placed around the perimeter of the domain with adjacent coils possessing alternating winding directions for optimum performance. The underlying current density maps from which the coils themselves are derived are unique, and optimized to possess minimal stored energy. Therefore, the method produces magnet designs with the lowest possible overall stored energy. Optimal coil layouts are provided for unshielded and shielded short bore symmetric superconducting magnets.
Fractional Order Magnetic Resonance Fingerprinting in the Human Cerebral Cortex
Publisher: MDPI AG
Date: 07-2021
DOI: 10.3390/MATH9131549
Abstract: Mathematical models are becoming increasingly important in magnetic resonance imaging (MRI), as they provide a mechanistic approach for making a link between tissue microstructure and signals acquired using the medical imaging instrument. The Bloch equations, which describes spin and relaxation in a magnetic field, are a set of integer order differential equations with a solution exhibiting mono-exponential behaviour in time. Parameters of the model may be estimated using a non-linear solver or by creating a dictionary of model parameters from which MRI signals are simulated and then matched with experiment. We have previously shown the potential efficacy of a magnetic resonance fingerprinting (MRF) approach, i.e., dictionary matching based on the classical Bloch equations for parcellating the human cerebral cortex. However, this classical model is unable to describe in full the mm-scale MRI signal generated based on an heterogenous and complex tissue micro-environment. The time-fractional order Bloch equations have been shown to provide, as a function of time, a good fit of brain MRI signals. The time-fractional model has solutions in the form of Mittag–Leffler functions that generalise conventional exponential relaxation. Such functions have been shown by others to be useful for describing dielectric and viscoelastic relaxation in complex heterogeneous materials. Hence, we replaced the integer order Bloch equations with the previously reported time-fractional counterpart within the MRF framework and performed experiments to parcellate human gray matter, which consists of cortical brain tissue with different cyto-architecture at different spatial locations. Our findings suggest that the time-fractional order parameters, α and β, potentially associate with the effect of interareal architectonic variability, which hypothetically results in more accurate cortical parcellation.
The design of planar gradient coils. Part II: A weighted superposition method
Publisher: Wiley
Date: 2005
DOI: 10.1002/CMR.B.20050
An impaired mitochondrial electron transport chain increases retention of the hypoxia imaging agent diacetylbis(4-methylthiosemicarbazonato)copperII.
Publisher: Proceedings of the National Academy of Sciences
Date: 15-12-2012
Abstract: Radiolabeled diacetylbis(4-methylthiosemicarbazonato)copper II [Cu II (atsm)] is an effective positron-emission tomography imaging agent for myocardial ischemia, hypoxic tumors, and brain disorders with regionalized oxidative stress, such as mitochondrial myopathy, encephalopathy, and lactic acidosis with stroke-like episodes (MELAS) and Parkinson’s disease. An excessively elevated reductive state is common to these conditions and has been proposed as an important mechanism affecting cellular retention of Cu from Cu II (atsm). However, data from whole-cell models to demonstrate this mechanism have not yet been provided. The present study used a unique cell culture model, mitochondrial xenocybrids, to provide whole-cell mechanistic data on cellular retention of Cu from Cu II (atsm). Genetic incompatibility between nuclear and mitochondrial encoded subunits of the mitochondrial electron transport chain (ETC) in xenocybrid cells compromises normal function of the ETC. As a consequence of this impairment to the ETC we show xenocybrid cells upregulate glycolytic ATP production and accumulate NADH. Compared to control cells the xenocybrid cells retained more Cu after being treated with Cu II (atsm). By transfecting the cells with a metal-responsive element reporter construct the increase in Cu retention was shown to involve a Cu II (atsm)-induced increase in intracellular bioavailable Cu specifically within the xenocybrid cells. Parallel experiments using cells grown under hypoxic conditions confirmed that a compromised ETC and elevated NADH levels contribute to increased cellular retention of Cu from Cu II (atsm). Using these cell culture models our data demonstrate that compromised ETC function, due to the absence of O 2 as the terminal electron acceptor or dysfunction of in idual components of the ETC, is an important determinant in driving the intracellular dissociation of Cu II (atsm) that increases cellular retention of the Cu.
Echo time‐dependent quantitative susceptibility mapping contains information on tissue properties
Publisher: Wiley
Date: 25-05-2016
DOI: 10.1002/MRM.26281
Abstract: Magnetic susceptibility is a physical property of matter that varies depending on chemical composition and abundance of different molecular species. Interest is growing in mapping of magnetic susceptibility in the human brain using magnetic resonance imaging techniques, but the influences affecting the mapped values are not fully understood. We performed quantitative susceptibility mapping on 7 Tesla (T) multiple echo time gradient recalled echo data and evaluated the trend in 10 regions of the human brain. Temporal plots of susceptibility were performed in the caudate, pallidum, putamen, thalamus, insula, red nucleus, substantia nigra, internal capsule, corpus callosum, and fornix. We implemented an existing three compartment signal model and used optimization to fit the experimental result to assess the influences that could be responsible for our findings. The temporal trend in susceptibility is different for different brain regions, and subsegmentation of specific regions suggests that differences are likely to be attributable to variations in tissue structure and composition. Using a signal model, we verified that a nonlinear temporal behavior in experimentally computed susceptibility within imaging voxels may be the result of the heterogeneous composition of tissue properties. Decomposition of voxel constituents into meaningful parameters may lead to informative measures that reflect changes in tissue microstructure. Magn Reson Med 77:1946–1958, 2017. © 2016 International Society for Magnetic Resonance in Medicine
Magnetic resonance imaging in nonlinear fields with nonlinear reconstruction
Publisher: Wiley
Date: 26-07-2011
DOI: 10.1002/CMR.B.20200
Multimodal image registration using stochastic differential equation optimization
Publisher: IEEE
Date: 09-2010
A Rapid Procedure for Spectral Similarity Matching of Heteronuclear Single Quantum Coherence Spectra
Publisher: IEEE
Date: 12-2011
Qualitative and Quantitave Analysis of Six Image Fusion Methodologies and Their Application to Medical Imaging
Publisher: IEEE
Date: 12-2011
MRI demodulation frequency changes provide different information
Publisher: Wiley
Date: 23-08-2011
DOI: 10.1002/MRM.23099
Compact Superconducting Magnet Design for Nuclear Magnetic Resonance
Publisher: Elsevier
Date: 2012
High-field magnetic resonance imaging using solenoid radiofrequency coils
Publisher: Elsevier BV
Date: 10-2012
DOI: 10.1016/J.MRI.2012.04.027
Abstract: High-resolution magnetic resonance imaging using dedicated high-field radiofrequency micro-coils at 16.4 T (700 MHz) was investigated. Specific solenoid coils primarily using silver and copper as conductors with enamel and polyurethane coatings were built to establish which coil configuration produces the best image. Image quality was quantified using signal-to-noise ratio and signal variation over regions of interest. Benchmarking was conducted using 5-mm diameter coils, as this size is comparable to an established coil of the same size. Our 1.4-mm-diameter coils were compared directly to each other, from which we deduce performance as a function of conductor material and coating. A variety of materials and conductor coatings allowed us to choose an optimal design, which we used to image a kidney section at 10-micron resolution. We applied zero-fill extrapolation to achieve 5-micron resolution.
The design of planar gradient coils. Part I: A winding path correction method
Publisher: Wiley
Date: 2005
DOI: 10.1002/CMR.B.20049
An adaptable mri radiofrequency breast coil: Evaluation of size, coil diameter, and uniformity
Publisher: Wiley
Date: 04-2012
DOI: 10.1002/CMR.B.21211
The challenge of bias‐free coil combination for quantitative susceptibility mapping at ultra‐high field
Publisher: Wiley
Date: 03-2017
DOI: 10.1002/MRM.26644
Abstract: Quantitative susceptibility mapping is a technique to estimate the magnetic property of tissue with particularly high sensitivity at ultra-high field. However, a key challenge at ultra-high field is the combination of phase data acquired using phased array receive coils. Several methods for combining phase data have been proposed, but the influence of coil combination choices on susceptibility quantitation has not been studied systematically. We combined phase data using COMPOSER (COMbining Phase data using a Short Echo-time Reference scan) and a reference-free channel-by-channel method. We investigated the effect of the chosen combination method on susceptibility results in a group of 28 participants at 7 Tesla. Our results show that reference scans can bias susceptibility values. Although the proposed reference-free channel-by-channel method cannot remove transmit field phase, it shows comparable results to the COMPOSER method in which a high-resolution ultrashort echo-time reference scan was used. We conclude that ultrashort echo-time reference scans reduce quantitation bias and remove the transmit field phase when using COMPOSER to combine phase data, and not combining the phase data before susceptibility processing avoids this bias, resulting in comparable results. Magn Reson Med 79:97-107, 2018. © 2017 InternationalSociety for Magnetic Resonance in Medicine.
A wrapped edge transverse gradient coil design for increased gradient homogeneity
Publisher: Wiley
Date: 08-2009
DOI: 10.1002/CMR.B.20140
The Use of Inverse Phase Fourier Image to Accommodate Intensity Inhomogeneities in Medical Image Registration
Publisher: IEEE
Date: 09-2012
Effective Protocol for Database Similarity Searching of Heteronuclear Single Quantum Coherence Spectra
Publisher: American Chemical Society (ACS)
Date: 26-10-2009
DOI: 10.1021/AC901616T
Abstract: The nuclear magnetic resonance (NMR) chemical shift exquisitely describes the chemical environment of the atoms in a molecule. Here we describe methods that utilize this information as an experimental probe to match 2D NMR heteronuclear single quantum coherence (HSQC) spectra of pure, unknown compounds to a database of known compounds. We implemented and compared two different approaches for similarity searching of HSQC spectra. According to our findings, our new discrete self-adaptive differential evolution method performs better than the previously published shifted grid, multiple resolution approach. The new method is provided in detail and comparisons have been performed for a set of HSQC spectra. The similarity comparison involves a peak-to-peak matching of different spectra, followed by a selection criterion and ranking to establish a level of match.
A CNN Based Software Gradiometer for Electromagnetic Background Noise Reduction in Low Field MRI Applications
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2022
A wave equation technique for designing compact gradient coils
Publisher: Wiley
Date: 2006
DOI: 10.1002/CMR.B.20061
Application of Weber's Law to Medical Image Registration to Accommodate Intensity Inhomogeneities
Publisher: IEEE
Date: 12-2012
A Variable Order Fractional Differential-Based Texture Enhancement Algorithm with Application in Medical Imaging
Publisher: Public Library of Science (PLoS)
Date: 17-07-2015
Minimum Stored Energy High-Field MRI Superconducting Magnets
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2009
An approach of deriving relative sensitivity profiles for image reconstruction in MRI
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2008
Monopole antenna array design for 3 T and 7 T magnetic resonance imaging
Publisher: Public Library of Science (PLoS)
Date: 04-2019
2D Frameworks of C2 N and C3 N as New Anode Materials for Lithium-Ion Batteries
Publisher: Wiley
Date: 10-07-2017
Abstract: Novel layered 2D frameworks (C 3 N and C 2 N‐450) with well‐defined crystal structures are explored for use as anode materials in lithium‐ion batteries (LIBs) for the first time. As anode materials for LIBs, C 3 N and C 2 N‐450 exhibit unusual electrochemical characteristics. For ex le, C 2 N‐450 (and C 3 N) display high reversible capacities of 933.2 (383.3) and 40.1 (179.5) mAh g −1 at 0.1 and 10 C, respectively. Furthermore, C 3 N shows a low hypothetical voltage (≈0.15 V), efficient operating voltage window with ≈85% of full discharge capacity secured at .45 V, and excellent cycling stability for more than 500 cycles. The excellent electrochemical performance (especially of C 3 N) can be attributed to their inherent 2D polyaniline frameworks, which provide large net positive charge densities, excellent structural stability, and enhanced electronic/ionic conductivity. Stable solid state interface films also form on the surfaces of the 2D materials during the charge/discharge process. These 2D materials with promising electrochemical performance should provide insights to guide the design and development of their analogues for future energy applications.
Persistent sodium current blockers can suppress seizures caused by loss of low‐threshold D‐type potassium currents: Predictions from an in silico study of Kv1 channel disorders
Publisher: Wiley
Date: 22-01-2020
DOI: 10.1002/EPI4.12379
Selective channel combination of MRI signal phase
Publisher: Wiley
Date: 24-11-2015
DOI: 10.1002/MRM.26057
Abstract: Signal magnitude can robustly be combined using the sum-of-squares approach. Methods have been developed to combine complex images. However, techniques based only on signal phase have not been developed and evaluated. We performed simulations to demonstrate the effect of noise on coil combination. 32-channel 7 Tesla human gradient echo MRI brain data were collected. We combined phase images based on phase noise leading to spatially selective and coil selective combination of phase images. We compared our selective combination approach to optimal noise distribution and adaptive combination methods. We found that selective combination of signal phases leads to improved phase signal-to-noise ratio. Furthermore, a phase shift can be present in combined phase images introduced by the method used to combine multiple channel phases. Mapping of signal phase from ultra-high field MRI data undoubtedly provides a wealth of information about the ageing brain and the effects of neurodegenerative disorders. Measurement of signal phase is essential in frequency shift mapping and in quantitative susceptibility mapping. The method used to combine signal phase should be informed by an understanding of the noise distribution in signal phase at the in idual channel level. Magn Reson Med 76:1469-1477, 2016. © 2015 International Society for Magnetic Resonance in Medicine.
Signal compartments in ultra-high field multi-echo gradient echo MRI reflect underlying tissue microstructure in the brain
Publisher: Elsevier BV
Date: 09-2018
DOI: 10.1016/J.NEUROIMAGE.2018.05.061
Abstract: Gradient recalled echo magnetic resonance imaging (GRE-MRI) at ultra-high field holds great promise for new contrast mechanisms and delineation of putative tissue compartments that contribute to the multi-echo GRE-MRI signal may aid structural characterization. Several studies have adopted the three water-pool compartment model to study white matter brain regions, associating in idual compartments with myelin, axonal and extracellular water. However, the number and identifiability of GRE-MRI signal compartments has not been fully explored. We undertook this task for human brain imaging data. Multiple echo time GRE-MRI data were acquired in five healthy participants, specific anatomical structures were segmented in each dataset (substantia nigra, caudate, insula, putamen, thalamus, fornix, internal capsule, corpus callosum and cerebrospinal fluid), and the signal fitted with models comprising one to six signal compartments using a complex-valued plane wave formulation. Information criteria and cluster analysis methods were used to ascertain the number of distinct compartments within the signal from each structure and to determine their respective frequency shifts. We identified five principal signal compartments with different relative contributions to each structure's signal. Voxel-based maps of the volume fraction of each of these compartments were generated and demonstrated spatial correlation with brain anatomy.
An unsupervised deep learning-based image translation method for retrospective motion correction of high resolution kidney MRI
Publisher: Elsevier BV
Date: 2023
Multi-term time-fractional Bloch equations and application in magnetic resonance imaging
Publisher: Elsevier BV
Date: 08-2017
MRI resolution enhancement: How useful are shifted images obtained by changing the demodulation frequency?
Publisher: Wiley
Date: 06-10-2011
DOI: 10.1002/MRM.22653
Abstract: Super-resolution reconstruction is a process by which a set of different low resolution images of the same object are used to create an enhanced, higher resolution image of that object. Recently there has been debate amongst researchers whether it is possible to obtain in-plane image enhancement using a set of low resolution magnetic resonance images, acquired by making small, independent changes to the demodulation frequency. We show that shifted low-resolution images contain different information that can be used to obtain denser s ling, leading to image enhancement. We conclude this from specific phantom experiments, applying signal processing s ling theory and taking into consideration the relative s ling of the point spread function with respect to the location of signal sources. Furthermore, the maximum achievable resolution for Fourier encoded MRI data at a boundary or object feature is governed by the effective width of the point spread function or the Fourier pixel size determined by the extent of k-space this is verified experimentally.
Efficient solution of linear inverse problems using an iterative linear neural network with a generalization training approach
Publisher: IOP Publishing
Date: 03-2021
Abstract: Inverse problems are some of the most important mathematical problems in science and mathematics because their solution yields information about parameters that are not directly observable. Artificial neural networks have long been used as a mathematical modelling method and have been used successfully to solve inverse problems for application including denoising and medical image reconstruction. Many inverse problems result from integral processes that can be modelled using a linear formulation. These can be efficiently solved via simple networks which are easily trained with reasonable datasets. An innovative simple neural network architecture, the iterative linear neural network (ILNN), consisting of two non-hidden layer networks, one for the forward model and one for the inverse model, is proposed to solve linear inverse problems. Iteration between the two models refines network outcomes with greater accuracy than a network with only the inverse model. A training procedure accompanying the network is also introduced. The network needs to train only the inverse model with one-hot vectors as targets. The training inputs of the inverse model define the weights of the forward model. The number of targets is finite and equal to the length of the vector. With the defined targets, the training process ensures that the inverse model is at least a left inverse of the forward model. This leads to generalizable networks. The experimental results show that the ILNN produces good results even if its inverse model is not perfectly trained. The proposed network is applied to solve two linear inverse problems, deconvolution and the inverse Radon transform. The network successfully reconstructed original data following blurring and Radon transformation.
Towards ultimate low frequency air-core magnetometer sensitivity
Publisher: Springer Science and Business Media LLC
Date: 23-05-2017
DOI: 10.1038/S41598-017-02099-Z
Abstract: Air-core magnetometers are amongst the most commonly used magnetic field detectors in biomedical instruments. They offer excellent sensitivity, low fabrication complexity and a robust, cost-effective solution. However, air-core magnetometers must be tailored to the specific application to achieve high sensitivity, which can be decisive in the accuracy of the diagnoses and the time required for the examination. Existing methods proposed for the design of air-core magnetometers are based on simplified models and simulations using a reduced number of variables, potentially leading to sensitivity that is suboptimal. To circumvent this we chose a method with fewer assumptions and a larger number of decision variables which employed a genetic algorithm, a global optimisation method. Experimental validation shows that the model is appropriate for the design of highly sensitive air-core magnetometers. Moreover, our results support the suitability of a genetic algorithm for optimization in this context. The new method described herein will be made publicly available via our website to facilitate the development of less costly biomedical instruments using air-core magnetometers with unprecedented sensitivity.
Iop-DWI: a novel scheme for pre-processing of diffusion-weighted images in le gradient direction domain
Publisher: Frontiers Media SA
Date: 12-01-2015
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Ulsan National Institute Of Science And Technology
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